技术领域Technical Field
本文件涉及图像处理领域，尤其涉及一种图像处理方法和装置。This document relates to the field of image processing, and in particular to an image processing method and device.
背景技术Background Art
随着硬件技术的升级和显示质量的提高，人们不再满足于已有的平面(2D)显示成像技术的需求，对于追求立体(3D)显示有着强烈的兴趣，目前各种电子产品均提供了一系列虚拟合成的伪3D显示效果，快捷、经济，实用的裸眼3D显示技术成为各路玩家在显示成像领域追求的终极目标。With the upgrading of hardware technology and the improvement of display quality, people are no longer satisfied with the existing flat (2D) display imaging technology and have a strong interest in the pursuit of stereoscopic (3D) display. Currently, various electronic products provide a series of virtual synthetic pseudo-3D display effects. Fast, economical and practical naked-eye 3D display technology has become the ultimate goal pursued by various players in the field of display imaging.
目前，双目相机拍摄及成像方法因为其高昂成本和高精度操作要求将裸眼3D成像技术一直集中在很少部分人手里；而利用独立图像拍摄进行融合的成像技术又因其成像质量不稳定，成像质量不高等原因受到发展瓶颈。因此裸眼3D成像技术在成本和质量两方面制约下难以实现质的突破，如何攻克这一难题，是技术人员日益关注的重点。At present, the high cost and high-precision operation requirements of binocular camera shooting and imaging methods have concentrated naked-eye 3D imaging technology in the hands of a small number of people; and the imaging technology that uses independent image shooting for fusion has been bottlenecked by its unstable and low imaging quality. Therefore, it is difficult for naked-eye 3D imaging technology to achieve a qualitative breakthrough under the constraints of cost and quality. How to overcome this problem is the focus of increasing attention of technicians.
发明内容Summary of the invention
本说明书一个实施例的目的是提供一种图像处理方法和装置，以解决图像融合质量不高的问题。An object of one embodiment of the present specification is to provide an image processing method and apparatus to solve the problem of low image fusion quality.
为解决上述技术问题，本说明书一个实施例是这样实现的：To solve the above technical problems, an embodiment of this specification is implemented as follows:
第一方面，本说明书一个实施例提供了一种图像处理方法，包括：In a first aspect, an embodiment of the present specification provides an image processing method, comprising:
对多个彩色深度图像进行深度对齐处理，获得多个深度对齐图像；Performing depth alignment processing on multiple color depth images to obtain multiple depth aligned images;
根据各深度对齐图像的比例尺确定所述各深度对齐图像的重叠区域和非重叠区域，并对所述各深度对齐图像的重叠区域进行特征点提取，获得所述重叠区域的特征点；Determine overlapping areas and non-overlapping areas of the depth alignment images according to the scales of the depth alignment images, and extract feature points from the overlapping areas of the depth alignment images to obtain feature points of the overlapping areas;
对所述重叠区域的特征点进行相似度匹配，获得所述各深度对齐图像的重叠特征点；Performing similarity matching on the feature points in the overlapping area to obtain overlapping feature points of the depth-aligned images;
基于所述各深度对齐图像的重叠特征点进行所述重叠区域的图像融合，获得融合区域，并对所述融合区域和所述非重叠区域进行拼接获得的拼接图像进行展示。The images of the overlapping area are fused based on the overlapping feature points of the depth alignment images to obtain a fused area, and a stitched image obtained by stitching the fused area and the non-overlapping area is displayed.
第二方面，本说明书另一个实施例提供了一种图像处理装置，包括：In a second aspect, another embodiment of the present specification provides an image processing device, including:
图像对齐模块，被配置为对多个彩色深度图像进行深度对齐处理，获得多个深度对齐图像；An image alignment module is configured to perform depth alignment processing on a plurality of color depth images to obtain a plurality of depth aligned images;
特征点提取模块，被配置为根据各深度对齐图像的比例尺确定所述各深度对齐图像的重叠区域和非重叠区域，并对所述各深度对齐图像的重叠区域进行特征点提取，获得所述重叠区域的特征点；A feature point extraction module is configured to determine the overlapping area and non-overlapping area of each depth alignment image according to the scale of each depth alignment image, and extract feature points from the overlapping area of each depth alignment image to obtain feature points of the overlapping area;
相似度匹配模块，被配置为对所述重叠区域的特征点进行相似度匹配，获得所述各深度对齐图像的重叠特征点；A similarity matching module is configured to perform similarity matching on the feature points of the overlapping area to obtain overlapping feature points of the depth aligned images;
图像融合模块，被配置为基于所述各深度对齐图像的重叠特征点进行所述重叠区域的图像融合，获得融合区域，并对所述融合区域和所述非重叠区域进行拼接获得的拼接图像进行展示。The image fusion module is configured to perform image fusion of the overlapping area based on the overlapping feature points of the depth alignment images to obtain a fused area, and display a stitched image obtained by stitching the fused area and the non-overlapping area.
第三方面，本说明书又一个实施例提供了一种图像处理设备，包括：存储器、处理器和存储在所述存储器上并可在所述处理器上运行的计算机可执行指令，所述计算机可执行指令被所述处理器执行时实现如上述第一方面所述的图像处理方法的步骤。In a third aspect, another embodiment of the present specification provides an image processing device, comprising: a memory, a processor, and computer executable instructions stored in the memory and executable on the processor, wherein the computer executable instructions, when executed by the processor, implement the steps of the image processing method as described in the first aspect above.
第四方面，本说明书再一个实施例提供了一种计算机可读存储介质，所述计算机可读存储介质用于存储计算机可执行指令，所述计算机可执行指令被处理器执行时实现如上述第一方面所述的图像处理方法的步骤。In a fourth aspect, another embodiment of the present specification provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store computer-executable instructions, and when the computer-executable instructions are executed by a processor, the steps of the image processing method described in the first aspect above are implemented.
本实施例提供的图像处理方法，在获取多个彩色深度图像后，对多个彩色深度图像进行深度对齐处理，获得多个深度对齐图像，然后根据各深度对齐图像的比例尺确定各深度对齐图像的重叠区域和非重叠区域，并对各深度对齐图像的重叠区域进行特征点提取，获得重叠区域的特征点，在此之后，对重叠区域的特征点进行相似度匹配，获得各深度对齐图像的重叠特征点，并基于各深度对齐图像的重叠特征点进行重叠区域的图像融合，获得融合区域，最后对融合区域和非重叠区域进行拼接获得的拼接图像进行展示，以此，通过缩短像素点特征提取运算的数据量，保证了特征提取的运算速度和准确性，确保了图像质量。The image processing method provided in the present embodiment performs depth alignment processing on the multiple color depth images after acquiring multiple color depth images to obtain multiple depth aligned images, then determines the overlapping area and non-overlapping area of each depth aligned image according to the scale of each depth aligned image, and extracts feature points from the overlapping area of each depth aligned image to obtain feature points of the overlapping area, then performs similarity matching on the feature points of the overlapping area to obtain overlapping feature points of each depth aligned image, and performs image fusion of the overlapping area based on the overlapping feature points of each depth aligned image to obtain a fused area, and finally displays a spliced image obtained by splicing the fused area and the non-overlapping area, thereby ensuring the operation speed and accuracy of the feature extraction and the image quality by shortening the data volume of the pixel feature extraction operation.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
为了更清楚地说明本说明书一个或多个实施例中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本说明书中记载的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。In order to more clearly illustrate the technical solutions in one or more embodiments of the present specification, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.
图1为本说明书一个实施例提供的一种图像处理方法处理流程图；FIG1 is a flowchart of an image processing method provided by an embodiment of the present specification;
图2为本说明书一个实施例提供的一种图像处理方法重叠特征点示意图；FIG2 is a schematic diagram of overlapping feature points of an image processing method provided by an embodiment of this specification;
图3为本说明书一个实施例提供的一种应用于裸眼3D成像场景的图像处理方法处理流程图；FIG3 is a processing flow chart of an image processing method applied to a naked-eye 3D imaging scene provided by one embodiment of this specification;
图4为本说明书一个实施例提供的一种图像处理装置示意图；FIG4 is a schematic diagram of an image processing device provided by an embodiment of this specification;
图5为本说明书一个实施例提供的一种图像处理设备的结构示意图。FIG. 5 is a schematic diagram of the structure of an image processing device provided by an embodiment of this specification.
具体实施方式DETAILED DESCRIPTION
为了使本技术领域的人员更好地理解本说明书一个或多个实施例中的技术方案，下面将结合本说明书一个或多个实施例中的附图，对本说明书一个或多个实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本说明书的一部分实施例，而不是全部的实施例。基于本说明书一个或多个实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都应当属于本文件的保护范围。In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below in conjunction with the drawings in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this document.
本说明书提供的一种图像处理方法实施例：An embodiment of an image processing method provided in this specification:
参照图1，本实施例提供的图像处理方法具体包括下述步骤S102至步骤S108。1 , the image processing method provided in this embodiment specifically includes the following steps S102 to S108 .
步骤S102，对多个彩色深度图像进行深度对齐处理，获得多个深度对齐图像。Step S102: performing depth alignment processing on a plurality of color depth images to obtain a plurality of depth aligned images.
本实施例中，通过图像采集设备对同一场景或同一物品进行不同角度的拍摄，获得多张具有交叉内容的彩色深度图像，其中，所述彩色深度图像，是指同时携带彩色值和深度值的图像，例如RGBD图像，此外，所述彩色深度图像还可以是彩色图像和深度图像的组合，例如普通相机拍摄的彩色图像与深度相机拍摄的深度图像的组合，此处，普通相机与深度相机的拍摄角度应相同。所述深度对齐图像，是指对彩色深度图像的深度信息进行对齐后得到的图像，对齐是指将多张彩色深度图像中同一像素点的深度值对齐到同一数值。In this embodiment, the same scene or the same object is photographed at different angles by an image acquisition device to obtain multiple color depth images with cross-content, wherein the color depth image refers to an image that carries both color values and depth values, such as an RGBD image. In addition, the color depth image can also be a combination of a color image and a depth image, such as a combination of a color image taken by an ordinary camera and a depth image taken by a depth camera. Here, the shooting angles of the ordinary camera and the depth camera should be the same. The depth alignment image refers to an image obtained by aligning the depth information of the color depth image, and alignment refers to aligning the depth values of the same pixel in multiple color depth images to the same value.
具体执行过程中，为了改善图像采集设备采集的图像的质量和清晰度，提高后续图像处理任务的准确性，通过对图像采集设备采集到的各图像的像素点数量进行检测的方式，针对性的对各图像进行预处理，提高图像质量，本实施例提供的一种可选实施方式中，图像采集设备采用如下方式进行彩色深度图像的采集：In the specific implementation process, in order to improve the quality and clarity of the images collected by the image acquisition device and improve the accuracy of subsequent image processing tasks, the number of pixels of each image collected by the image acquisition device is detected to pre-process each image in a targeted manner to improve the image quality. In an optional implementation manner provided in this embodiment, the image acquisition device acquires the color depth image in the following manner:
检测通过图像采集设备采集到的各图像的像素点数量是否达到阈值；Detecting whether the number of pixels of each image acquired by the image acquisition device reaches a threshold;
若所述像素点数量小于所述阈值，则对所述各图像的像素点进行数据补全处理，获得所述多个彩色深度图像；If the number of pixels is less than the threshold, performing data completion processing on the pixels of each image to obtain the multiple color depth images;
若所述像素点数量大于所述阈值，则对所述各图像的像素点进行数据降噪处理，获得所述多个彩色深度图像。If the number of pixels is greater than the threshold, data noise reduction processing is performed on the pixels of each image to obtain the multiple color depth images.
其中，所述图像是指未经过预处理的图像，在获取到图像采集设备采集到未经过预处理的图像之后，通过预处理对未经过预处理的图像进行数据补全处理和/或数据降噪处理，获得彩色深度图像，具体的，检测各图像的像素点数量是否达到阈值；若像素点数量小于阈值，则对各图像的像素点进行数据补全处理，获得多个彩色深度图像；若像素点数量大于阈值，则对各图像的像素点进行数据降噪处理，获得多个彩色深度图像。Among them, the image refers to an image that has not been preprocessed. After the image acquisition device acquires the image that has not been preprocessed, the image that has not been preprocessed is preprocessed and/or data noise reduction is performed on the image to obtain a color depth image. Specifically, it is detected whether the number of pixels of each image reaches a threshold; if the number of pixels is less than the threshold, data completion is performed on the pixels of each image to obtain multiple color depth images; if the number of pixels is greater than the threshold, data noise reduction is performed on the pixels of each image to obtain multiple color depth images.
示例的，数据补全处理可根据缺失的像素点的近邻像素点使用最小近邻法或者4近邻平均加权法对缺失的像素点进行填补处理，以补全像素点；数据降噪处理可使用白噪声消除方法对像素点进行降噪处理，通过还原像素点的颜色值，使得该像素点的像素值可用于后续的处理。For example, the data completion processing can use the least neighbor method or the 4-neighbor average weighted method to fill in the missing pixels according to the neighboring pixels of the missing pixels to complete the pixels; the data denoising processing can use the white noise elimination method to denoise the pixels, and by restoring the color value of the pixel, the pixel value of the pixel can be used for subsequent processing.
具体在对采集到的彩色深度图像进行预处理之后，还需对彩色深度图像的深度值进行调整，由于图像的深度信息可能因采集设备参数调整或者采集环境变动而存在误差，为了使后续进行展示的图像更加准确，通过采集设备的聚焦位置对彩色深度图像的深度值进行调整，使得多张彩色深度图像中同一个像素点的深度值可以对齐，本实施例提供的一种可选实施方式中，采用如下方式对多个彩色深度图像进行深度对齐处理：Specifically, after the collected color depth image is preprocessed, the depth value of the color depth image needs to be adjusted. Since the depth information of the image may have errors due to the adjustment of the acquisition device parameters or the change of the acquisition environment, in order to make the subsequent displayed image more accurate, the depth value of the color depth image is adjusted by the focus position of the acquisition device so that the depth values of the same pixel in multiple color depth images can be aligned. In an optional implementation manner provided in this embodiment, the depth alignment processing of multiple color depth images is performed in the following manner:
若所述多个彩色深度图像的深度值的差距大于预设阈值，则标定所述多个彩色深度图像的聚焦位置；If the difference between the depth values of the plurality of color depth images is greater than a preset threshold, calibrating the focus positions of the plurality of color depth images;
根据所述聚焦位置调整所述多个彩色深度图像的深度值，获得所述多个深度对齐图像。The depth values of the multiple color depth images are adjusted according to the focus position to obtain the multiple depth aligned images.
具体的，使用同一个图像采集设备在同一角度采集的彩色深度图像的深度值应该是相同的，但是实际中，往往因为采集设备参数调整或者采集环境变动等原因导致彩色深度图像的深度值不一致，在这种情况下，就需要依据聚焦位置对彩色深度图像的深度值进行调整；Specifically, the depth values of the color depth images collected at the same angle using the same image acquisition device should be the same. However, in practice, the depth values of the color depth images are often inconsistent due to reasons such as adjustment of acquisition device parameters or changes in the acquisition environment. In this case, the depth value of the color depth image needs to be adjusted according to the focus position.
其中，所述聚焦位置是指图像中心点的焦点位置，对图像的深度值进行调整之前需要先选择参考图像对图像的聚焦位置进行标定，当彩色深度图像只有两个时，选择两个图像中深度值较高的图像作为参考图像，进行聚焦位置的标定，当彩色深度图像有多个时，对多个彩色深度图像进行图像聚焦的评估，选择评估结果最好的图像作为参考图像，通过标定聚焦位置使得不同图像的焦点位置一致，再基于标定的聚焦位置和参考图像，对其他图像进行后续的深度值调整，以此获得所述多个深度对齐图像。Among them, the focus position refers to the focus position of the center point of the image. Before adjusting the depth value of the image, it is necessary to select a reference image to calibrate the focus position of the image. When there are only two color depth images, select the image with a higher depth value of the two images as the reference image to calibrate the focus position. When there are multiple color depth images, evaluate the image focusing of the multiple color depth images, and select the image with the best evaluation result as the reference image. By calibrating the focus position, the focus positions of different images are made consistent, and then based on the calibrated focus position and the reference image, subsequent depth value adjustments are performed on other images to obtain the multiple depth-aligned images.
具体的，深度值差距的阈值可针对不同的需求设置，对深度值的差距大于深度值差距的阈值的图像标定该图像的聚焦位置，根据该聚焦位置调整图像的深度值，直至将深度值调整到小于深度值差距的阈值，示例的，深度值差距的阈值可以设置为5％，对深度值的差距大于5％的图像标定聚焦位置时，可使用相机聚焦方式中的黑白间隔棋盘进行图像聚焦位置的标定，标定完成后确定图像的像素间隔总数和棋盘间隔的对应关系，基于该像素间隔总数和棋盘间隔的对应关系对图像的深度值进行调整处理，直至深度值的差距小于5％。Specifically, the threshold of the depth value difference can be set according to different needs. For an image whose depth value difference is greater than the threshold of the depth value difference, the focus position of the image is calibrated, and the depth value of the image is adjusted according to the focus position until the depth value is adjusted to be less than the threshold of the depth value difference. For example, the threshold of the depth value difference can be set to 5%. When calibrating the focus position of an image whose depth value difference is greater than 5%, the black and white interval chessboard in the camera focus mode can be used to calibrate the image focus position. After the calibration is completed, the correspondence between the total number of pixel intervals and the chessboard intervals of the image is determined, and the depth value of the image is adjusted based on the correspondence between the total number of pixel intervals and the chessboard intervals until the depth value difference is less than 5%.
步骤S104，根据各深度对齐图像的比例尺确定所述各深度对齐图像的重叠区域和非重叠区域，并对所述各深度对齐图像的重叠区域进行特征点提取，获得所述重叠区域的特征点。Step S104 : determining the overlapping area and the non-overlapping area of each depth alignment image according to the scale of each depth alignment image, and extracting feature points from the overlapping area of each depth alignment image to obtain feature points of the overlapping area.
上述对多个彩色深度图像进行深度对齐处理，获得多个深度对齐图像之后，本步骤中，根据各深度对齐图像的各个深度值对应的比例尺确定各深度对齐图像的重叠区域和非重叠区域，并对其中的重叠区域进行特征点提取，获得重叠区域的特征点。After the depth alignment process is performed on the multiple color depth images to obtain multiple depth aligned images, in this step, the overlapping area and non-overlapping area of each depth aligned image are determined according to the scale corresponding to each depth value of each depth aligned image, and feature points are extracted from the overlapping area to obtain feature points of the overlapping area.
所述比例尺，是指图像的深度值相等的像素个数和棋盘间隔数的对应关系，在上述通过黑白间隔棋盘进行图像焦距位置的标定的过程中，已经确定了深度对齐图像的比例尺，需要说明的是，彩色深度图像中不同深度值的像素点对应有不同的待处理区域，在确定各深度对齐图像的各待处理区域之后，即可根据各待处理区域各自的比例尺对所述待处理区域的区域边界进行修正，并基于修正后的各待处理区域确定所述重叠区域和非重叠区域，本实施例提供的一种可选实施方式中，采用如下方式根据各深度对齐图像的比例尺确定所述各深度对齐图像的重叠区域和非重叠区域：The scale refers to the correspondence between the number of pixels with equal depth values in the image and the number of chessboard intervals. In the above process of calibrating the focal length position of the image by the black and white interval chessboard, the scale of the depth alignment image has been determined. It should be noted that pixels with different depth values in the color depth image correspond to different areas to be processed. After determining each area to be processed of each depth alignment image, the area boundary of the area to be processed can be corrected according to the scale of each area to be processed, and the overlapping area and non-overlapping area are determined based on the corrected areas to be processed. In an optional implementation manner provided in this embodiment, the overlapping area and non-overlapping area of each depth alignment image are determined according to the scale of each depth alignment image in the following manner:
根据所述各深度对齐图像的像素点的深度值确定所述各深度对齐图像的各待处理区域；Determine each to-be-processed area of each depth-aligned image according to the depth values of the pixel points of each depth-aligned image;
根据所述各待处理区域各自的比例尺对所述待处理区域的区域边界进行修正，并基于修正后的各待处理区域确定所述重叠区域和非重叠区域。The region boundaries of the regions to be processed are corrected according to the respective scales of the regions to be processed, and the overlapping regions and the non-overlapping regions are determined based on the corrected regions to be processed.
具体的，由于彩色深度图像中不同区域的深度值不同，所以可以根据深度对齐图像的像素点的深度值确定各深度对齐图像的各待处理区域，并根据各待处理区域各自的比例尺对待处理区域的区域边界进行修正，并基于修正后的各待处理区域确定重叠区域和非重叠区域，此处重叠区域是指两张或两张以上的彩色深度图像有交叉内容的区域，例如，图像a中包含物体1，物体2和物体2，图像b中也包含物体1，物体2以及物体4，那么图像a和图像b的重叠区域即为物体1所在的区域和物体2所在的区域。Specifically, since the depth values of different areas in the color depth image are different, the areas to be processed of each depth aligned image can be determined according to the depth values of the pixels of the depth aligned image, and the area boundaries of the areas to be processed can be corrected according to the scales of the areas to be processed, and the overlapping areas and non-overlapping areas can be determined based on the corrected areas to be processed. The overlapping area here refers to an area where two or more color depth images have overlapping content. For example, image a contains object 1, object 2 and object 2, and image b also contains object 1, object 2 and object 4. Then the overlapping area of image a and image b is the area where object 1 is located and the area where object 2 is located.
进一步，在根据各深度对齐图像的像素点的深度值确定各深度对齐图像的各待处理区域的过程中，本实施例提供的一种可选实施方式中，可以采用如下方式获取各深度对齐图像的各待处理区域中任一待处理区域：Further, in the process of determining each to-be-processed area of each depth-aligned image according to the depth value of the pixel point of each depth-aligned image, in an optional implementation manner provided by this embodiment, any to-be-processed area of each to-be-processed area of each depth-aligned image can be obtained in the following manner:
筛选出深度值一致的像素点作为待处理像素点；Filter out pixels with consistent depth values as pixels to be processed;
根据所述待处理像素点的聚集度对所述待处理像素点中的边缘像素点进行剔除，获得有效像素点，并将包含所述有效像素点的区域作为所述待处理区域。According to the concentration degree of the pixels to be processed, edge pixels in the pixels to be processed are eliminated to obtain valid pixels, and a region including the valid pixels is used as the region to be processed.
具体的，由于深度对齐图像中同一区域的深度值通常一致，但是深度值一致的像素点中可能存在不聚集于同一区域的边缘像素点，所以在筛选出深度值一致的像素点作为待处理像素点之后，需根据待处理像素点的聚集度对待处理像素点中的边缘像素点进行剔除，获得有效像素点，并将包含所述有效像素点的区域作为所述待处理区域。Specifically, since the depth values of the same area in the depth-aligned image are usually consistent, but there may be edge pixels that are not concentrated in the same area among the pixels with consistent depth values, after screening out the pixels with consistent depth values as the pixels to be processed, it is necessary to eliminate the edge pixels in the pixels to be processed according to the concentration of the pixels to be processed, obtain valid pixels, and use the area containing the valid pixels as the area to be processed.
例如，图像a中物体1的深度值为x，并且物体1处于图像a的左上角，且在图像a的中部存在2个深度值为x的像素点，图像a的右下部存在3个深度值为x的像素点，所以在获取待处理区域的过程中，首先筛选出图像a中深度值为x的像素点作为待处理像素点，然后根据待处理像素点聚集在图像a的左上角的特征，将图像a的中部存在的2个深度值为x的像素点以及图像a的右下部存在的3个深度值为x的像素点进行剔除，获得图像a的左上角深度值为x的像素点的聚集区域作为待处理区域，此外，图像中其他深度值也做上述处理，本实施例在此不再赘述。For example, the depth value of object 1 in image a is x, and object 1 is in the upper left corner of image a, and there are 2 pixels with a depth value of x in the middle of image a, and there are 3 pixels with a depth value of x in the lower right part of image a. Therefore, in the process of obtaining the area to be processed, the pixels with a depth value of x in image a are first screened out as the pixels to be processed, and then, based on the feature that the pixels to be processed are concentrated in the upper left corner of image a, the 2 pixels with a depth value of x in the middle of image a and the 3 pixels with a depth value of x in the lower right part of image a are eliminated, and the concentrated area of pixels with a depth value of x in the upper left corner of image a is obtained as the area to be processed. In addition, the above processing is also performed on other depth values in the image, which will not be repeated in this embodiment.
具体执行过程中，在确定各深度对齐图像的重叠区域之后，对重叠区域进行特征点提取，具体可采用金字塔模型或者优化金字塔模型进行特征提取，以一张深度对齐图像为例，首先，将深度对齐图像作为金字塔的第一层，称为原始层，然后，通过对原始层进行高斯平滑操作，生成下一层，即较低分辨率的深度对齐图像，重复上述步骤，直到达到所需的金字塔层数或图像的尺寸达到最小限制，在此之后，即可对每个层级的图像进行特征提取，常用的特征提取方法包括边缘检测、角点检测、纹理分析等，可以使用各种图像处理和视觉算法来实现特征提取。In the specific implementation process, after determining the overlapping area of each depth-aligned image, feature points are extracted from the overlapping area. Specifically, a pyramid model or an optimized pyramid model can be used for feature extraction. Taking a depth-aligned image as an example, first, the depth-aligned image is used as the first layer of the pyramid, called the original layer. Then, the original layer is Gaussian smoothed to generate the next layer, that is, a depth-aligned image with a lower resolution. The above steps are repeated until the required number of pyramid layers is reached or the image size reaches the minimum limit. After that, feature extraction can be performed on images at each level. Common feature extraction methods include edge detection, corner detection, texture analysis, etc. Various image processing and visual algorithms can be used to achieve feature extraction.
步骤S106，对所述重叠区域的特征点进行相似度匹配，获得所述各深度对齐图像的重叠特征点。Step S106: performing similarity matching on the feature points in the overlapping area to obtain overlapping feature points of the depth-aligned images.
上述根据各深度对齐图像的比例尺确定各深度对齐图像的重叠区域和非重叠区域，并对各深度对齐图像的重叠区域进行特征点提取，获得重叠区域的特征点之后，本步骤中，对重叠区域的特征点进行相似度匹配，获得各深度对齐图像的重叠特征点。The above-mentioned method determines the overlapping area and non-overlapping area of each depth aligned image according to the scale of each depth aligned image, and extracts feature points of the overlapping area of each depth aligned image. After obtaining the feature points of the overlapping area, in this step, similarity matching is performed on the feature points of the overlapping area to obtain the overlapping feature points of each depth aligned image.
具体执行过程中，为了使提高图像描述的可靠性以及降低计算复杂度，在获得重叠区域的特征点之后，可以对特征点进行筛选，基于特征维数较高的特征点进行后续的相似度匹配操作，本实施例提供的一种可选实施方式中，采用如下方式对重叠区域的特征点进行相似度匹配，获得各深度对齐图像的重叠特征点：In the specific implementation process, in order to improve the reliability of image description and reduce the computational complexity, after obtaining the feature points of the overlapping area, the feature points can be screened, and subsequent similarity matching operations are performed based on feature points with higher feature dimensions. In an optional implementation provided by this embodiment, similarity matching is performed on the feature points of the overlapping area in the following manner to obtain overlapping feature points of each depth aligned image:
根据所述特征点的特征维数对所述重叠区域的特征点进行筛选，获得目标特征点；Screening the feature points of the overlapping area according to the feature dimensions of the feature points to obtain target feature points;
采用相似度匹配算法对所述目标特征点进行相似度匹配，获得所述重叠特征点。A similarity matching algorithm is used to perform similarity matching on the target feature points to obtain the overlapping feature points.
具体的，在获得重叠区域的特征点之后，可以按照特征点的特征维数对特征点进行排序，取序列中处于预设位次的特征点进行相似度匹配，在进行相似度匹配的过程中，可以采用尺度不变特征变换方法或其优化方法进行相似度匹配，找到各深度对齐图像的重叠区域的重叠特征点，需要说明的是各深度对齐图像的重叠特征点是一一对应的关系。Specifically, after obtaining the feature points of the overlapping area, the feature points can be sorted according to their feature dimensions, and the feature points in the sequence at a preset position are taken for similarity matching. In the process of similarity matching, a scale-invariant feature transformation method or an optimization method thereof can be used for similarity matching to find the overlapping feature points of the overlapping areas of each depth-aligned image. It should be noted that the overlapping feature points of each depth-aligned image are in a one-to-one correspondence.
例如，如图2展示的重叠特征点示意图中所示，在确定两张深度对齐图像的重叠区域之后，对左图的重叠区域与右图的重叠区域分别进行特征点提取，获得左图中黑色特征点和白色特征点，和与之对应的右图中的黑色特征点和白色特征点，其中左图中的黑色特征点与右图中的黑色特征点即为黑色重叠特征点，左图中的白色特征点与右图中的白色特征点即为白色重叠特征点。For example, as shown in the schematic diagram of overlapping feature points shown in Figure 2, after determining the overlapping area of the two depth aligned images, feature points are extracted for the overlapping area of the left image and the overlapping area of the right image respectively to obtain black feature points and white feature points in the left image, and the corresponding black feature points and white feature points in the right image, wherein the black feature points in the left image and the black feature points in the right image are black overlapping feature points, and the white feature points in the left image and the white feature points in the right image are white overlapping feature points.
步骤S108，基于所述各深度对齐图像的重叠特征点进行所述重叠区域的图像融合，获得融合区域，并对所述融合区域和所述非重叠区域进行拼接获得的拼接图像进行展示。Step S108 , performing image fusion of the overlapping area based on the overlapping feature points of the depth alignment images to obtain a fused area, and displaying a stitched image obtained by stitching the fused area and the non-overlapping area.
上述对重叠区域的特征点进行相似度匹配，获得各深度对齐图像的重叠特征点之后，本步骤中，基于各深度对齐图像的重叠特征点进行所述重叠区域的图像融合，获得融合区域，并对融合区域和非重叠区域进行拼接获得的拼接图像进行展示。After the similarity matching is performed on the feature points of the overlapping areas to obtain the overlapping feature points of each depth aligned image, in this step, image fusion of the overlapping areas is performed based on the overlapping feature points of each depth aligned image to obtain a fused area, and a stitched image obtained by stitching the fused area and the non-overlapping area is displayed.
具体执行过程中，在获得重叠特征点之后，可利用投影变化原理，将各重叠特征点的坐标位置进行统一，以进行图像融合，本实施例提供的一种可选实施方式中，采用如下方式基于各深度对齐图像的重叠特征点进行重叠区域的图像融合，获得融合区域：In the specific implementation process, after obtaining the overlapping feature points, the coordinate positions of the overlapping feature points can be unified by using the projection change principle to perform image fusion. In an optional implementation provided by this embodiment, the image fusion of the overlapping area is performed based on the overlapping feature points of each depth alignment image in the following manner to obtain the fusion area:
将所述重叠特征点中任一特征点作为基准特征点，并计算所述重叠特征点中其他特征点与所述基准特征点的位移矢量；Taking any feature point among the overlapping feature points as a reference feature point, and calculating a displacement vector between other feature points among the overlapping feature points and the reference feature point;
基于所述位移矢量确定所述重叠特征点中各特征点在二维坐标系中的坐标，并根据所述坐标进行所述重叠区域的图像融合，获得所述融合区域。The coordinates of each feature point in the overlapping feature points in a two-dimensional coordinate system are determined based on the displacement vector, and the images of the overlapping area are fused according to the coordinates to obtain the fused area.
具体的，从深度对齐图像中选择一个作为参考图像，选择参考图像中的一个重叠特征点作为基准特征点，对于每个与之对应的重叠特征点，根据其与所述基准特征点的位移矢量，可以通过投影变换将重叠特征点转换到同一个二维坐标(世界坐标)下，在此之后，可以使用拉普拉斯金字塔，或者高斯融合等图像融合方法对图像进行融合Specifically, one of the depth aligned images is selected as a reference image, and an overlapping feature point in the reference image is selected as a reference feature point. For each overlapping feature point corresponding to it, according to its displacement vector with the reference feature point, the overlapping feature point can be transformed to the same two-dimensional coordinate (world coordinate) by projection transformation. After that, the image fusion method such as Laplacian pyramid or Gaussian fusion can be used to fuse the image.
以两张图像的重叠区域通过拉普拉斯金字塔融合为例，首先，将两个图像的重叠区域分别构建成拉普拉斯金字塔，拉普拉斯金字塔是通过对原始图像进行多次降采样和上采样得到的图像金字塔，每一层图像是原始图像与上一层图像上采样后的差值，然后将两个图像的对应金字塔层进行融合，可以选择简单的加权平均或者其他融合策略，最后，将融合后的金字塔层级通过逐层上采样和累加得到最终融合后的融合区域。Taking the fusion of the overlapping areas of two images through the Laplacian pyramid as an example, first, the overlapping areas of the two images are constructed into Laplacian pyramids respectively. The Laplacian pyramid is an image pyramid obtained by multiple downsampling and upsampling of the original image. Each layer of the image is the difference between the original image and the previous layer after upsampling. Then, the corresponding pyramid layers of the two images are fused. Simple weighted average or other fusion strategies can be selected. Finally, the fused pyramid levels are upsampled and accumulated layer by layer to obtain the final fused fusion area.
下述结合附图3，以本实施例提供的图像处理方法在裸眼3D成像场景的应用为例，对本实施例提供的图像处理方法进行进一步说明。参照图3，应用于裸眼3D成像场景的图像处理方法具体包括步骤S302至步骤S326。The image processing method provided by this embodiment is further described below by taking the application of the image processing method provided by this embodiment in the naked eye 3D imaging scene as an example in conjunction with FIG3. Referring to FIG3, the image processing method applied to the naked eye 3D imaging scene specifically includes steps S302 to S326.
步骤S302，检测通过图像采集设备采集到的各图像的像素点数量是否达到阈值。Step S302: Detect whether the number of pixels of each image acquired by the image acquisition device reaches a threshold.
步骤S304，若像素点数量小于阈值，则对各图像的像素点进行数据补全处理，获得多个彩色深度图像。Step S304: if the number of pixels is less than the threshold, data completion processing is performed on the pixels of each image to obtain a plurality of color depth images.
步骤S306，若像素点数量大于阈值，则对各图像的像素点进行数据降噪处理，获得多个彩色深度图像。Step S306: If the number of pixels is greater than the threshold, data noise reduction processing is performed on the pixels of each image to obtain multiple color depth images.
步骤S308，若多个彩色深度图像的深度值的差距大于预设阈值，则标定多个彩色深度图像的聚焦位置。Step S308 : if the difference between the depth values of the plurality of color depth images is greater than a preset threshold, calibrate the focus positions of the plurality of color depth images.
步骤S310，根据聚焦位置调整多个彩色深度图像的深度值，获得多个深度对齐图像。Step S310: adjusting depth values of a plurality of color depth images according to a focus position to obtain a plurality of depth aligned images.
步骤S312，根据各深度对齐图像的像素点的深度值确定各深度对齐图像的各待处理区域。Step S312: determining each to-be-processed area of each depth-aligned image according to the depth values of the pixels of each depth-aligned image.
步骤S314，根据各待处理区域各自的比例尺对待处理区域的区域边界进行修正，并基于修正后的各待处理区域确定重叠区域和非重叠区域。Step S314: correcting the region boundaries of the regions to be processed according to the scales of the regions to be processed, and determining overlapping regions and non-overlapping regions based on the corrected regions to be processed.
步骤S316，对各深度对齐图像的重叠区域进行特征点提取，获得重叠区域的特征点。Step S316: extract feature points from the overlapping areas of the depth aligned images to obtain feature points of the overlapping areas.
步骤S318，根据特征点的特征维数对重叠区域的特征点进行筛选，获得目标特征点。Step S318, screening the feature points in the overlapping area according to the feature dimensions of the feature points to obtain target feature points.
步骤S320，采用相似度匹配算法对目标特征点进行相似度匹配，获得重叠特征点。Step S320: perform similarity matching on the target feature points using a similarity matching algorithm to obtain overlapping feature points.
步骤S322，将重叠特征点中任一特征点作为基准特征点，并计算重叠特征点中其他特征点与基准特征点的位移矢量Step S322: taking any feature point in the overlapping feature points as a reference feature point, and calculating the displacement vector between the other feature points in the overlapping feature points and the reference feature point.
步骤S324，基于位移矢量确定重叠特征点中各特征点在二维坐标系中的坐标，并根据坐标进行重叠区域的图像融合，获得融合区域。Step S324, determining the coordinates of each feature point in the overlapping feature points in the two-dimensional coordinate system based on the displacement vector, and performing image fusion of the overlapping area according to the coordinates to obtain a fused area.
步骤S326，对融合区域和非重叠区域进行拼接获得的拼接图像进行展示。Step S326, displaying a stitched image obtained by stitching the fused area and the non-overlapping area.
图4为本发明一实施例提供的一种图像处理装置示意图，如图4所示，该装置包括：FIG4 is a schematic diagram of an image processing device provided by an embodiment of the present invention. As shown in FIG4 , the device includes:
图像对齐模块402，被配置为对多个彩色深度图像进行深度对齐处理，获得多个深度对齐图像；The image alignment module 402 is configured to perform depth alignment processing on the multiple color depth images to obtain multiple depth aligned images;
特征点提取模块404，被配置为根据各深度对齐图像的比例尺确定所述各深度对齐图像的重叠区域和非重叠区域，并对所述各深度对齐图像的重叠区域进行特征点提取，获得所述重叠区域的特征点；The feature point extraction module 404 is configured to determine the overlapping area and the non-overlapping area of each depth alignment image according to the scale of each depth alignment image, and extract feature points from the overlapping area of each depth alignment image to obtain feature points of the overlapping area;
相似度匹配模块406，被配置为对所述重叠区域的特征点进行相似度匹配，获得所述各深度对齐图像的重叠特征点；A similarity matching module 406 is configured to perform similarity matching on the feature points of the overlapping area to obtain overlapping feature points of the depth aligned images;
图像融合模块408，被配置为基于所述各深度对齐图像的重叠特征点进行所述重叠区域的图像融合，获得融合区域，并对所述融合区域和所述非重叠区域进行拼接获得的拼接图像进行展示。The image fusion module 408 is configured to perform image fusion of the overlapping area based on the overlapping feature points of the depth alignment images to obtain a fused area, and display a stitched image obtained by stitching the fused area and the non-overlapping area.
本实施例提供的图像处理方法，首先通过运行图像对齐模块402，对多个彩色深度图像进行深度对齐处理，获得多个深度对齐图像，以及运行特征点提取模块404，根据各深度对齐图像的比例尺确定所述各深度对齐图像的重叠区域和非重叠区域，并对所述各深度对齐图像的重叠区域进行特征点提取，获得所述重叠区域的特征点，进一步，在得到重叠区域的特征点之后，运行相似度匹配模块406，对所述重叠区域的特征点进行相似度匹配，获得所述各深度对齐图像的重叠特征点，再运行图像融合模块408，基于所述各深度对齐图像的重叠特征点进行所述重叠区域的图像融合，获得融合区域，并对所述融合区域和所述非重叠区域进行拼接获得的拼接图像进行展示，以此，通过缩短像素点特征提取运算的数据量，保证了特征提取的运算速度和准确性，确保了图像质量。The image processing method provided in this embodiment firstly performs depth alignment processing on multiple color depth images by running an image alignment module 402 to obtain multiple depth alignment images, and runs a feature point extraction module 404 to determine the overlapping area and non-overlapping area of each depth alignment image according to the scale of each depth alignment image, and extracts feature points from the overlapping area of each depth alignment image to obtain the feature points of the overlapping area. Furthermore, after obtaining the feature points of the overlapping area, runs a similarity matching module 406 to perform similarity matching on the feature points of the overlapping area to obtain the overlapping feature points of the depth alignment images, and then runs an image fusion module 408 to perform image fusion of the overlapping area based on the overlapping feature points of the depth alignment images to obtain a fused area, and displays a spliced image obtained by splicing the fused area and the non-overlapping area. In this way, by shortening the data amount of pixel feature extraction operation, the operation speed and accuracy of feature extraction are guaranteed, and the image quality is ensured.
本说明书一实施例提供的图像处理装置能够实现前述方法实施例中的各个过程，并达到相同的功能和效果，这里不再重复。The image processing device provided in one embodiment of the present specification can implement each process in the aforementioned method embodiment and achieve the same functions and effects, which will not be repeated here.
进一步地，本说明书一个实施例还提供了一种图像处理设备，图5为本说明书一实施例提供的一种图像处理设备的结构示意图，如图5所示，该设备包括：存储器501、处理器502、总线503和通信接口504。存储器501、处理器502和通信接口504通过总线503进行通信，通信接口504可以包括输入输出接口，输入输出接口包括但不限于键盘、鼠标、显示器、麦克风、扩音器等。Furthermore, an embodiment of the present specification also provides an image processing device. FIG5 is a schematic diagram of the structure of an image processing device provided in an embodiment of the present specification. As shown in FIG5, the device includes: a memory 501, a processor 502, a bus 503, and a communication interface 504. The memory 501, the processor 502, and the communication interface 504 communicate via the bus 503. The communication interface 504 may include an input and output interface, and the input and output interface includes but is not limited to a keyboard, a mouse, a display, a microphone, a loudspeaker, and the like.
图5中，所述存储器501上存储有可以在所述处理器502上运行的计算机可执行指令，所述计算机可执行指令被所述处理器502执行时实现以下流程：In FIG5 , the memory 501 stores computer executable instructions that can be run on the processor 502. When the computer executable instructions are executed by the processor 502, the following process is implemented:
对多个彩色深度图像进行深度对齐处理，获得多个深度对齐图像；Performing depth alignment processing on multiple color depth images to obtain multiple depth aligned images;
根据各深度对齐图像的比例尺确定所述各深度对齐图像的重叠区域和非重叠区域，并对所述各深度对齐图像的重叠区域进行特征点提取，获得所述重叠区域的特征点；Determine overlapping areas and non-overlapping areas of the depth alignment images according to the scales of the depth alignment images, and extract feature points from the overlapping areas of the depth alignment images to obtain feature points of the overlapping areas;
对所述重叠区域的特征点进行相似度匹配，获得所述各深度对齐图像的重叠特征点；Performing similarity matching on the feature points in the overlapping area to obtain overlapping feature points of the depth-aligned images;
基于所述各深度对齐图像的重叠特征点进行所述重叠区域的图像融合，获得融合区域，并对所述融合区域和所述非重叠区域进行拼接获得的拼接图像进行展示。The images of the overlapping area are fused based on the overlapping feature points of the depth alignment images to obtain a fused area, and a stitched image obtained by stitching the fused area and the non-overlapping area is displayed.
本实施例提供的图像处理设备，通过存储器501、处理器502、总线503和通信接口504的配合，在获取多个彩色深度图像后，对多个彩色深度图像进行深度对齐处理，获得多个深度对齐图像，然后根据各深度对齐图像的比例尺确定各深度对齐图像的重叠区域和非重叠区域，并对各深度对齐图像的重叠区域进行特征点提取，获得重叠区域的特征点，在此之后，对重叠区域的特征点进行相似度匹配，获得各深度对齐图像的重叠特征点，并基于各深度对齐图像的重叠特征点进行重叠区域的图像融合，获得融合区域，最后对融合区域和非重叠区域进行拼接获得的拼接图像进行展示，以此，通过缩短像素点特征提取运算的数据量，保证了特征提取的运算速度和准确性，确保了图像质量。The image processing device provided in this embodiment, through the cooperation of the memory 501, the processor 502, the bus 503 and the communication interface 504, after acquiring multiple color depth images, performs depth alignment processing on the multiple color depth images to obtain multiple depth aligned images, then determines the overlapping area and non-overlapping area of each depth aligned image according to the scale of each depth aligned image, and extracts feature points from the overlapping area of each depth aligned image to obtain feature points of the overlapping area, then performs similarity matching on the feature points of the overlapping area to obtain overlapping feature points of each depth aligned image, and performs image fusion of the overlapping area based on the overlapping feature points of each depth aligned image to obtain a fused area, and finally displays a spliced image obtained by splicing the fused area and the non-overlapping area, thereby ensuring the speed and accuracy of feature extraction and image quality by shortening the data volume of pixel feature extraction operation.
本说明书一实施例提供的图像处理设备能够实现前述方法实施例中的各个过程，并达到相同的功能和效果，这里不再重复。The image processing device provided in one embodiment of the present specification can implement each process in the aforementioned method embodiment and achieve the same functions and effects, which will not be repeated here.
进一步地，本说明书另一个实施例还提供了一种计算机可读存储介质，所述计算机可读存储介质用于存储计算机可执行指令，所述计算机可执行指令被处理器执行时实现以下流程：Furthermore, another embodiment of the present specification provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store computer-executable instructions, and when the computer-executable instructions are executed by a processor, the following process is implemented:
对多个彩色深度图像进行深度对齐处理，获得多个深度对齐图像；Performing depth alignment processing on multiple color depth images to obtain multiple depth aligned images;
根据各深度对齐图像的比例尺确定所述各深度对齐图像的重叠区域和非重叠区域，并对所述各深度对齐图像的重叠区域进行特征点提取，获得所述重叠区域的特征点；Determine overlapping areas and non-overlapping areas of the depth alignment images according to the scales of the depth alignment images, and extract feature points from the overlapping areas of the depth alignment images to obtain feature points of the overlapping areas;
对所述重叠区域的特征点进行相似度匹配，获得所述各深度对齐图像的重叠特征点；Performing similarity matching on the feature points in the overlapping area to obtain overlapping feature points of the depth-aligned images;
基于所述各深度对齐图像的重叠特征点进行所述重叠区域的图像融合，获得融合区域，并对所述融合区域和所述非重叠区域进行拼接获得的拼接图像进行展示。The images of the overlapping area are fused based on the overlapping feature points of the depth alignment images to obtain a fused area, and a stitched image obtained by stitching the fused area and the non-overlapping area is displayed.
本实施例提供的计算机可读存储介质，在获取多个彩色深度图像后，对多个彩色深度图像进行深度对齐处理，获得多个深度对齐图像，然后根据各深度对齐图像的比例尺确定各深度对齐图像的重叠区域和非重叠区域，并对各深度对齐图像的重叠区域进行特征点提取，获得重叠区域的特征点，在此之后，对重叠区域的特征点进行相似度匹配，获得各深度对齐图像的重叠特征点，并基于各深度对齐图像的重叠特征点进行重叠区域的图像融合，获得融合区域，最后对融合区域和非重叠区域进行拼接获得的拼接图像进行展示，以此，通过缩短像素点特征提取运算的数据量，保证了特征提取的运算速度和准确性，确保了图像质量。The computer-readable storage medium provided in the present embodiment performs depth alignment processing on the multiple color depth images after acquiring multiple color depth images to obtain multiple depth aligned images, then determines the overlapping area and non-overlapping area of each depth aligned image according to the scale of each depth aligned image, and extracts feature points from the overlapping area of each depth aligned image to obtain feature points of the overlapping area, then performs similarity matching on the feature points of the overlapping area to obtain overlapping feature points of each depth aligned image, and performs image fusion of the overlapping area based on the overlapping feature points of each depth aligned image to obtain a fused area, and finally displays a spliced image obtained by splicing the fused area and the non-overlapping area, thereby ensuring the speed and accuracy of feature extraction and image quality by shortening the data volume of pixel feature extraction operation.
其中，所述计算机可读存储介质包括只读存储器(Read-Only Memory，简称ROM)、随机存取存储器(Random Access Memory，简称RAM)、磁碟或者光盘等。The computer-readable storage medium includes a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.
本说明书一实施例提供的计算机可读存储介质能够实现前述方法实施例中的各个过程，并达到相同的功能和效果，这里不再重复。The computer-readable storage medium provided in an embodiment of this specification can implement each process in the aforementioned method embodiment and achieve the same functions and effects, which will not be repeated here.
本领域内的技术人员应明白，本发明的实施例可提供为方法、系统、或计算机程序产品。因此，本发明可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本发明可采用在一个或多个其中包含有计算机可用程序代码的计算机可读存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
本发明是参照根据本发明实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。The present invention is described with reference to the flowchart and/or block diagram of the method, device (system), and computer program product according to the embodiment of the present invention. It should be understood that each process and/or box in the flowchart and/or block diagram, as well as the combination of the process and/or box in the flowchart and/or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.
在一个典型的配置中，计算设备包括一个或多个处理器(CPU)、输入/输出接口、网络接口和内存。In a typical configuration, a computing device includes one or more processors (CPU), input/output interfaces, network interfaces, and memory.
内存可能包括计算机可读存储介质中的非永久性存储器，随机存取存储器(RAM)和/或非易失性内存等形式，如只读存储器(ROM)或闪存(flash RAM)。内存是计算机可读存储介质的示例。Memory may include non-permanent storage in a computer-readable storage medium, random access memory (RAM) and/or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable storage medium.
计算机可读存储介质包括永久性和非永久性、可移动和非可移动媒体可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。计算机可读存储介质的例子包括，但不限于相变内存(PRAM)、静态随机存取存储器(SRAM)、动态随机存取存储器(DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(CD-ROM)、数字多功能光盘(DVD)或其他光学存储、磁盒式磁带，磁带磁盘存储或其他磁性存储设备或任何其他非传输介质，可用于存储可以被计算设备访问的信息。按照本文中的界定，计算机可读存储介质不包括暂存电脑可读媒体(transitory media)，如调制的数据信号和载波。Computer-readable storage media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer-readable storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable storage media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.
还需要说明的是，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、商品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、商品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、商品或者设备中还存在另外的相同要素。It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.
本领域技术人员应明白，本申请的实施例可提供为方法、系统或计算机程序产品。因此，本申请可采用完全硬件实施例、完全软件实施例或结合软件和硬件方面的实施例的形式。而且，本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.
以上所述仅为本申请的实施例而已，并不用于限制本申请。对于本领域技术人员来说，本申请可以有各种更改和变化。凡在本申请的精神和原理之内所作的任何修改、等同替换、改进等，均应包含在本申请的权利要求范围之内。The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
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