A gradient-based optimization approach for reduction of blocking artifacts in JPEG images

Abstract

This paper presents a gradient-based optimization approach to achieve reduction of blocking artifacts in compressed JPEG images. This approach involves decomposing a JPEG image into 1-D signals once along the rows or columns and once along the columns or rows. The reduction of blocking artifacts is carried out per 1-D signal by an optimization formulation where the gradient of an original 1-D signal is approximated based on the gradient of a compressed signal. A fixed-weight and an adaptive-weight optimization formulation are considered and solved analytically. A restored image is reconstructed by aggregating recovered 1-D signals. The performance of the developed method is assessed by examining both gray-level and color images and by computing the three measures of PSNR, SSIM, and GBIM. Comparison results with five existing methods are also reported.