Image Blur Removal By Adaptive Filtering

Digital image processing DIP has many significant advantages over analog image processing. DIP allows a much wider range of algorithms to treat the impairment effects such as the build-up of blurred and noisy signal distortion during the diverse image processes. This paper is to assess couple of adaptive filters in estimating an image out of blur distortion. The image is distorted with Motion blur and Gaussian blur separately. The utilized restoration techniques are Lucy Richardson LR Algorithm filter and Wiener filter WF. The proposed filters are tested against the color image. Different performance measures are employed including Mean Square Error MSE Performance Index PI and Peak Signal-to-Noise Ratio PSNR. Repeatedly these measures show that LR filter demonstrates a much higher performance than its counterpart. In fact this filter outcome shows a decent match between subjective and objective assessments of the images.