Hierarchical Dynamic Range Coding of Wavelet Subbands for Fast and Efficient Image Decompression

TLDR: An image coding algorithm, progressive resolution coding (PROGRES), for a high-speed resolution scalable decoding is proposed, designed based on a prediction of the decaying dynamic ranges of wavelet subbands, which validates the suitability of the proposed method to very large scale image encoding and decoding.

Abstract: An image coding algorithm, progressive resolution coding (PROGRES), for a high-speed resolution scalable decoding is proposed. The algorithm is designed based on a prediction of the decaying dynamic ranges of wavelet subbands. Most interestingly, because of the syntactic relationship between two coders, the proposed method costs an amount of bits very similar to that used by uncoded (i.e., not entropy coded) SPIHT. The algorithm bypasses bit-plane coding and complicated list processing of SPIHT in order to obtain a considerable speed improvement, giving up quality scalability, but without compromising coding efficiency. Since each tree of coefficients is separately coded, where the root of the tree corresponds to the coefficient in LL subband, the algorithm is easily extensible to random access decoding. The algorithm is designed and implemented for both 2D and 3D wavelet subbands. Experiments show that the decoding speeds of the proposed coding model are four times and nine times faster than uncoded 2D-SPIHT and 3D-SPIHT, respectively, with almost the same decoded quality. The higher decoding speed gain in a larger image source validates the suitability of the proposed method to very large scale image encoding and decoding. In the Appendix, we explain the syntactic relationship of the proposed PROGRES method to uncoded SPIHT, and demonstrate that, in the lossless case, the bits sent to the codestream for each algorithm are identical, except that they are sent in different order.