IMAGE RESTORATION AND DEBLURRING USING LUCY RICHARDSON TECHNIQUE WITH WEINER AND REGULARIZED FILTER
Abstract

Author(s): Himanshu Joshi, Dr. Jitendra Sheetlani

Nowadays we are using high quality of digital camera for capturing the image but due to some artifacts the quality of images degrades such as noise so to restore its original quality different interpo lation techniques has implemented in digital image processing such as blind and non-blind restoration methods of image. In this work, we mainly emphasis on the Lucy Richardson algorithm and blind deconvolution using Weiner and regularized filter to restore the original image. The Lucy-Richardson algorithm engenders reconstructed images of improved quality in the existence of high noise level. Weiner deconvolution can be useful for the point spread function (PSF) when the noise level is known or estimated while regularized deconvolution is much more effective once constraints are applied on the recuperated image (for example: smoothness). The distorted and piercing image is restored by a constant least square (CLS) algorithm that uses regularized filter. The analysis of the projected approach is done using PSNR and MSE measuring parameters and after analysis it is found that the approach better in both the view visual quality and computation time view than other interpolation techniques. By using the combined method of image restoration and interpolation we obtained the better spatial resolution than others

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