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Simulation of Image Processing and Restoration Through A Base Image Using Matlab

Deepshikha Sahu, Ankita Sharma


Basically, in image processing the main work is done on pixels and its value. Basically, an image is a two-dimensional function f(x, y), where x and y are spatial coordinates. Here, in the present study geometrical transformation is being used for image restoration and processing. Steps are carried some for the result outcome. First the image is read in the algorithm, further the coordinates and pixels are being specified, and then it is geometrically transformed at a 31 degree. Further the inliers and outliers are being matched and a restored image is obtained. The mean square error (MSE) and Peak square noise ratio (PSNR) will also be studied. The study is based on Matlab algorithm m-file. The imaging systems have wide use among number of applications, including commercial photography, microscopy, aerial photography, astronomical and space imaging, etc. Many a times the output images or a video suffers from blur due to lenses, transmission medium, algorithms or a camera/person motion. The amount of blur can be measured and it’s an important issue. Image processing and restoration is a technique to enhance the quality of an image or a video, using some methods and processes.


Digital, imaging systems, algorithms, visual quality, restoration, fine feature

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