Add RISC-V HAL implementation for cv::norm and cv::normalize#26804This patch implements `cv::norm` with norm types `NORM_INF/NORM_L1/NORM_L2/NORM_L2SQR` and `Mat::convertTo` function in RVV_HAL using native intrinsic, optimizing the performance for `cv::norm(src)`, `cv::norm(src1, src2)`, and `cv::normalize(src)` with data types `8UC1/8UC4/32FC1`.`cv::normalize` also calls `minMaxIdx`,#26789 implements RVV_HAL for this.Tested on MUSE-PI for both gcc 14.2 and clang 20.0.```$ opencv_test_core --gtest_filter="*Norm*"$ opencv_perf_core --gtest_filter="*norm*" --perf_min_samples=300 --perf_force_samples=300```The head of the perf table is shown below since the table is too long.View the full perf table here: [hal_rvv_norm.pdf](https://github.com/user-attachments/files/18468255/hal_rvv_norm.pdf)<img width="1304" alt="Untitled" src="https://github.com/user-attachments/assets/3550b671-6d96-4db3-8b5b-d4cb241da650" />### Pull Request Readiness ChecklistSee details athttps://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request- [x] I agree to contribute to the project under Apache 2 License.- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV- [ ] The PR is proposed to the proper branch- [ ] There is a reference to the original bug report and related work- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable      Patch to opencv_extra has the same branch name.- [ ] The feature is well documented and sample code can be built with the project CMake

Add RISC-V HAL implementation for minMaxIdxopencv#26789On the RISC-V platform, `minMaxIdx` cannot benefit from Universal Intrinsics because the UI-optimized `minMaxIdx` only supports `CV_SIMD128` (and does not accept `CV_SIMD_SCALABLE` for RVV).https://github.com/opencv/opencv/blob/1d701d1690b8cc9aa6b86744bffd5d9841ac6fd3/modules/core/src/minmax.cpp#L209-L214This patch implements `minMaxIdx` function in RVV_HAL using native intrinsic, optimizing the performance for all data types with one channel.Tested on MUSE-PI for both gcc 14.2 and clang 20.0.```$ opencv_test_core --gtest_filter="*MinMaxLoc*"$ opencv_perf_core --gtest_filter="*minMaxLoc*"```<img width="1122" alt="Untitled" src="https://github.com/user-attachments/assets/6a246852-87af-42c5-a50b-c349c2765f3f" />See details athttps://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request- [x] I agree to contribute to the project under Apache 2 License.- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV- [ ] The PR is proposed to the proper branch- [ ] There is a reference to the original bug report and related work- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable      Patch to opencv_extra has the same branch name.- [ ] The feature is well documented and sample code can be built with the project CMake

Add RISC-V HAL implementation for cv::norm and cv::normalizeopencv#26804This patch implements `cv::norm` with norm types `NORM_INF/NORM_L1/NORM_L2/NORM_L2SQR` and `Mat::convertTo` function in RVV_HAL using native intrinsic, optimizing the performance for `cv::norm(src)`, `cv::norm(src1, src2)`, and `cv::normalize(src)` with data types `8UC1/8UC4/32FC1`.`cv::normalize` also calls `minMaxIdx`,opencv#26789 implements RVV_HAL for this.Tested on MUSE-PI for both gcc 14.2 and clang 20.0.```$ opencv_test_core --gtest_filter="*Norm*"$ opencv_perf_core --gtest_filter="*norm*" --perf_min_samples=300 --perf_force_samples=300```The head of the perf table is shown below since the table is too long.View the full perf table here: [hal_rvv_norm.pdf](https://github.com/user-attachments/files/18468255/hal_rvv_norm.pdf)<img width="1304" alt="Untitled" src="https://github.com/user-attachments/assets/3550b671-6d96-4db3-8b5b-d4cb241da650" />See details athttps://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request- [x] I agree to contribute to the project under Apache 2 License.- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV- [ ] The PR is proposed to the proper branch- [ ] There is a reference to the original bug report and related work- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable      Patch to opencv_extra has the same branch name.- [ ] The feature is well documented and sample code can be built with the project CMake