Deblurring of Motion Blurred Images Using GLCM and Elastic Net Regularization

Abstract

An image deburring algorithm consists of rich edge area mining with a gray-level co-occurring matrix and elastic net regularisation is proposed in this paper. First, the luminance channel of an image is removed from the blurred image. The frequency layer is highthat can be derived from the blurred image by converting the 2D haar wavelet in the luminance channel.By the way, measurements were made using area and the richest edge region information is then collected. Finally, the extracted rich edge field, instead full motion blurred image, approximate the blur kernel elastic net regularisation and the image is returned. A measurement of image mechanism and running time measures the proposed system. Result suggestedto recommended strategy would improve efficiency and ensure continuity in recovery.