Embedded image coding based on hierarchical discrete cosine transform

We illustrate that the zerotree quantizer developed originally for wavelet compression can be 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. Another level DCT is applied to only DC coefficients re-organized as 8×8 blocks. 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. 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 at low bit rates, a method based on Sobel operators is developed. Experimental results show that the proposed deblocking method works well and enhances decoding for decompressed images.