Joint thresholding and quantizer selection for decoder-compatible baseline JPEG
This paper introduces a novel, image-adaptive, encoding scheme for the baseline JPEG standard. In particular, coefficient thresholding, JPEG quantization matrix (Q-matrix) optimization, and adaptive Huffman entropy-coding are jointly performed to maximize coded still-image quality within the constraints of the baseline JPEG syntax. Adaptive JPEG coding has been addressed in earlier works: by Ramchandran and Vetterli (see IEEE Trans. on Image Processing, Special Issue on Image Compression, vol.3, p.700-704, September 1994), where fast rate-distortion (R-D) optimal coefficient thresholding was described, and by Wu and Gersho (see Proc. Inter. Conf. Acoustics, Speech and Signal Processing, vol.5, p.389-392, April 1993) and Hung and Meng (1991), where R-D optimized Q-matrix selection was performed. By formulating an algorithm which optimizes these two operations jointly, we have obtained performance comparable to more complex, "state-of-the-art" coding schemes: for the "Lenna" image at 1 bpp, our algorithm has achieved a PSNR of 39.6 dB. This result represents a gain of 1.7 dB over JPEG with a customized Huffman entropy coder, and even slightly exceeds the published performance of Shapiro's (see IEEE Trans. on Signal Processing, vol.41, p.3445-3462, December 1993) wavelet-based scheme. Furthermore, with the choice of appropriate visually-based error metrics, noticeable subjective improvement has been achieved as well.