Locally Adaptive Perceptual Compression for Color Images

Abstract

The main idea in perceptual image compression is to remove the perceptual redundancy for representing images at the lowest possible bit rate without introducing perceivable distortion. A certain amount of perceptual redundancy is inherent in the color image since human eyes are not perfect sensors for discriminating small differences in color signals. Effectively exploiting the perceptual redundancy will help to improve the coding efficiency of compressing color images. In this paper, a locally adaptive perceptual compression scheme for color images is proposed. The scheme is based on the design of an adaptive quantizer for compressing color images with the nearly lossless visual quality at a low bit rate. An effective way to achieve the nearly lossless visual quality is to shape the quantization error as a part of perceptual redundancy while compressing color images. This method is to control the adaptive quantization stage by the perceptual redundancy of the color image. In this paper, the perceptual redundancy in the form of the noise detection threshold associated with each coefficient in each subband of three color components of the color image is derived based on the finding of perceptually indistinguishable regions of color stimuli in the uniform color space and various masking effects of human visual perception. The quantizer step size for the target coefficient in each color component is adaptively adjusted by the associated noise detection threshold to make sure that the resulting quantization error is not perceivable. Simulation results show that the compression performance of the proposed scheme using the adaptively coefficient-wise quantization is better than that using the band-wise quantization. The nearly lossless visual quality of the reconstructed image can be achieved by the proposed scheme at lower entropy.