Blur removal using blind deconvolution and gradient energy
M. Ramesh Kanthan, S. Naganandini Sujatha · 2016
This The major contributions of this paper focus on an efficient method for blur removal which is an important preprocessing in high level image processing applications such as pattern recognition or object identification. The process of deconvolution along with edge preservation using Gradient energy has designed particularly for blur removal application like Fog, Haze, Rainy fog and blurry medical Images enhancement. The proposed algorithm has divided the image into number of homogeneous regions in a manner consistent with human perception. The image edge and region identification are somehow difficult in foggy images due to the blurriness. The robust algorithm using deconvolution and gradient energy are proposed for low contrast image classification. The algorithm efficiency of the proposed method tested with object contour and also compared with manual boundary identification.