An efficient technique for image compression and quality retrieval using matrix completion

In this paper, an efficient technique for image compression and quality retrieval using matrix completion is presented. The proposed technique is based on low-rank matrix completion using singular value trun-cation and thresholding. Here, an image is decomposed using singular value decomposition (SVD) to obtain a low rank of image data, which is approximated in compressed form. Later on, singular value thresholding algorithm is exploited to retrieve visual quality of the compressed image. The presented method is easily applicable for various visual characteristics of the image for different compression effi-ciency. A detailed analysis has been presented to show the efficiency of proposed method in term of com-pression as well as quality retrieval. It is evident from experimental results that a maximum of 80% compression is achieved with acceptable visual quality as per human vision system (HVS).(c) 2019 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).