Analysis and Improvement of Image Quality in De - Blocked Images

Image quality is a characteristic of an image that measures the perceived image degradation (typically, compared to an ideal or perfect image). Imaging systems may introduce some amounts of distortion or artifacts in the signal, so the quality assessment is an important problem JPEG compression is the most prevalent technique or method for image codec’s. But it suffers from blocking artifacts. In this paper a comparison of the perceptual quality of de-blocked images based on various quality assessments metric is done. We study the efficiency of deblocking algorithms for improving visual signals degraded by blocking artifacts from compression. Rather than using only the perceptually questionable PSNR, we instead propose a block-sensitive index, named PSNR-B, that produces objective judgments that accord with observations. The PSNR-B modifies PSNR by including a blocking effect factor. We also use the perceptually significant SSIM index, which produces results largely in agreement with PSNR-B. Simulation results show that the PSNR-B results in better performance for quality assessment of deblocked images than PSNR and a wellknown blockiness-specific index.