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How to Display an Image in Grayscale in Matplotlib?

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Python | Working with PNG Images using Matplotlib

Last Updated :11 Jul, 2025

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Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack. It was introduced by John Hunter in the year 2002.One of the greatest benefits of visualization is that it allows us visual access to huge amounts of data in easily digestible visuals. Matplotlib consists of several plots like line, bar, scatter, histogram etc. In this article, we will see how can we work with PNG images using Matplotlib.Code #1: Read a PNG image using Matplotlib

# importing pyplot and image from matplotlibimportmatplotlib.pyplotaspltimportmatplotlib.imageasimg# reading png image fileim=img.imread('imR.png')# show imageplt.imshow(im)

Code #2: Applying pseudocolor to image Pseudocolor is useful for enhancing contrast of image.

# importing pyplot and image from matplotlibimportmatplotlib.pyplotaspltimportmatplotlib.imageasimg# reading png imageim=img.imread('imR.png')# applying pseudocolor# default value of colormap is used.lum=im[:,:,0]# show imageplt.imshow(lum)

Code #3: We can provide another value to colormap with colorbar.

# importing pyplot and image from matplotlibimportmatplotlib.pyplotaspltimportmatplotlib.imageasimg# reading png imageim=img.imread('imR.png')lum=im[:,:,0]# setting colormap as hotplt.imshow(lum,cmap='hot')plt.colorbar()

Interpolation Schemes: Interpolation calculates what the color or value of a pixel “should” be and this needed when we resize the image but want the same information. There's missing space when you resize image because pixels are discrete and interpolation is how you fill that space.Code # 4: Interpolation

# importing PIL and matplotlibfromPILimportImageimportmatplotlib.pyplotasplt# reading png image  fileimg=Image.open('imR.png')# resizing the imageimg.thumbnail((50,50),Image.ANTIALIAS)imgplot=plt.imshow(img)

Code #6:Here, 'bicubic' value is used for interpolation.

# importing pyplot from matplotlibimportmatplotlib.pyplotasplt# importing image from PILfromPILimportImage# reading imageimg=Image.open('imR.png')img.thumbnail((30,30),Image.ANTIALIAS)# bicubic used for interpolationimgplot=plt.imshow(img,interpolation='bicubic')

Code #7:'sinc' value is used for interpolation.

# importing PIL and matplotlibfromPILimportImageimportmatplotlib.pyplotasplt# reading imageimg=Image.open('imR.png')img.thumbnail((30,30),Image.ANTIALIAS)# sinc used for interpolationimgplot=plt.imshow(img,interpolation='sinc')

Reference:https://matplotlib.org/stable/gallery/images_contours_and_fields/interpolation_methods.html

How to Display an Image in Grayscale in Matplotlib?

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