Post-processing enhancement of decompressed images using variable order Bezier polynomials and distance transform

Abstract

Summary form only given. We post-process images compressed by lossy JPEG algorithms (DCT and LOGO), following decompression, using Bezier polynomials for enhancement. Both JPEG algorithms, namely the DCT-based JPEG and the near-lossless baseline JPEG-LS (aka LOGO), employ spatial quantization. The DCT-based version introduces an artifact known as mosaic or blockiness by coarsely quantizing the DC coefficients. By quantizing the prediction errors, JPEG-LS introduces a banding artifact specially noticeable for quantization coarser than 8-off. The human visual system (HVS) is specially sensitive to degradations on smooth regions in the image. We propose a post-processing algorithm based on blending for enhancement of the degraded smooth regions due to quantization. In this work, we use Bezier polynomials of variable orders. Enhancement is obtained by blending each pixel in low-activity regions so the artifacts are reduced. The coefficients of the Bezier polynomials for the various orders used (from 3rd to 7th order) are precomputed and stored in look-up tables for speed. Active pixels, detected by using a threshold of 3/2 of the quantization step size, are left alone. The threshold is theoretically justified, avoids the problem of threshold determination on ordinary segmentation, and excludes quantization noise. In order to avoid over-smoothing of large low activity regions, the Bezier polynomials' order used to blend each pixel P/sub o,j/ is variable. Results are presented for lossy JPEG and JPEG-LS images for very low bit-rates.