Simulation of Image Processing using Linux Operating Systems
Image processing and restoration through a base image can provide useful information about the scene, such as saliency and depth map. We first apply the geometric transformation algorithm for restoration of the blurred image. As suggested in the base paper that the geometric analysis will provide us the fine feature available in the image, we have utilized this algorithm for the purpose of image restoration. Measuring the amount of blur globally and locally is an important issue. It can help us in eliminating the spatially changing haze and upgrading the visual nature of the imaging framework yields. While advanced imaging frameworks have been generally utilized for some, applications including customer photography, microscopy, aeronautical photography, galactic imaging, and so forth, their yield pictures/recordings regularly suﬀer from spatially fluctuating haze brought about by focal point, transmission medium, post handling calculations, and camera/object movement.
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