Embedded Image Coding Based on Hierarchical Discrete Cosine Transform
基于层次DCT变换的嵌入式图像编码方法

In this paper, we illustrate that the zerotree quantizer developed originally for wavelet compression can be effectively applied to Discrete Cosine Transform (DCT) in a hierarchical way. In this Hierarchical DCT (HDCT), the input image is partitioned into a number of 8×8 blocks and a first level DCT is used to each of these blocks individually. As DC coefficients of DCT neighboring blocks are highly correlated and particularly pronounced to obtain the compression results at low bit rates, another level DCT is applied to only DC coefficients re-organized as 8×8 blocks. This procedure is repeated until the last step is reached. All the HDCT coefficients within a DCT block are then rearranged into a sub-band structure in which the zerotree quantizer can be employed. The proposed algorithm yields a fully embedded, low-complexity coder with competitive PSNR performance. For example, when compared with the baseline JPEG on the 512×512 standard image "Lena”, it gains 0.8 dB～1.7 dB. In order to remove the blocking effects in the reconstructed images, especially at low bit rates, a simple and efficient method based on Sobel operators is also developed. Experimental results show that the proposed deblocking method works well and enhances decoding for decompressed images both objectively and subjectively.