Nonlinear constrained least squares estimation to reduce artifacts in block transform-coded images
This paper introduces a novel estimation scheme for reducing blocking artifacts in highly compressed, block-transformed images, such as those in JPEG or MPEG. We tackle the blockiness problem by performing constrained least squares (CLS) in the transform domain. Although the CLS approach has been addressed in previous work, we introduce a different approach with many desirable properties, including simple nonlinear processing to protect edges, efficient characterization of blockiness, and fast convergence. Using this new approach, we have obtained significant objective PSNR improvement over previous CLS work. Perceptually, we find significantly reduced blockiness by estimating only a few key transform coefficients per block, giving good visual quality with quick estimation.