Image Deblurring for Uniform Linear Motion

Images and videos frequently experience blurring caused by camera shake, and addressing this issue remains a significant challenge and active research focus in the field of image processing. One simplified approach involves implementing algorithms designed specifically for uniform linear motion deblurring. This method effectively reduces image blurring artifacts and enhances the quality of both images and videos. The implementation typically involves estimating the motion blur kernel (point spread function) along a single direction and applying deconvolution algorithms like Wiener filter or Richardson-Lucy deconvolution. By processing the shake-induced blur, we can obtain clearer, sharper images and videos, significantly improving the viewing experience. Key implementation steps include motion trajectory estimation, blur kernel modeling, and iterative restoration algorithms that can be programmed using image processing libraries like OpenCV or MATLAB's Image Processing Toolbox.