Enriched framework to remove camera shake in Blurred images using Gaussian kernel grazing method

Sonali Bhujbal, Vishal Gite, Dhanashree Magar, Ajay Gupta


Camera shaking is a problem which leads to blur images and many photographs. This causes object present in the image unclear. The deblurring methods the Convolution of a sharp image with a uniform blur kernel, Conventional blind deconvolution are used to give a better visualization of the image. It typically assumes frequency-domain contraints on image for motion path during shaking. These camera motions follow the given path and try to gives a clear visual. There is no such system which uniformly or equally removes the blurness. So this paper introduces the idea of weighted fourier burst accumulation method for resolving camera shake problem. The proposed algorithm performs a weighted average in fourier domain. The weights are based on the fourier spectrum magnitude. Photoshop is a one of system which use to remove the blur of an image .It is mostly use software mechanism which automatically reduce image blurring caused by camera motion.

Keywords: Block formation; Gaussian kernel; equivalent blur kernel estimation; reverse kernel application.

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Copyright (c) 2016 Sonali Bhujbal, Vishal Gite, Dhanashree Magar, Ajay Gupta

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