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

• The block-based processing in JPEG as well as the quantization of DCT coefficients cause blocking artifacts in compressed JPEG images which become more visible at low quantization levels.
• This paper presents a gradient-based optimization approach to achieve reduction of blocking artifacts.
• The approach involves deblocking along rows and columns (treated as 1-D signals) by an optimization formulation which involves either a fixed-weight or an adaptive-weight.
• The optimization formulation is solved analytically using the information provided by the approximated gradient of original 1-D signals.
• A blocking artifacts reduced image is reconstructed by aggregating 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, GBIM, and SSIM.

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.