In this paper, a research progress on applying adaptive secondary transform set in the context of ongoing next-generation video coding standardization beyond AV1 (namely AV2) of AOM (Alliance for Open Media) is presented. In the current reference software of AV2, namely AVM (AOM Video Model), secondary transform set is chosen mode-dependently and the index of the selected secondary transform kernel within a given transform set is signaled into the bitstream with the minimum bit cost. With the proposed method, the encoder is empowered with the capability of selecting any transform sets from multiple candidates. Experiment results demonstrate that the proposed method contributes to improving the overall video coding efficiency. The average coding gains measured in weighted YUV PSNR and SSIM BD-Rates are observed as 0.20% and 0.62% respectively for All Intra (AI) configuration of AOM CTC (Common Test Condition) v4 with AVM software of research anchor v4. Coding gains for the higher resolutions 4K and 2K are larger, 0.29% and 0.23% respectively.

Daala is a new royalty-free video codec that attempts to compete with state-of-the-art royalty-bearing codecs. To do so, it must achieve good compression while avoiding all of their patented techniques. We use technology that is as different as possible from traditional approaches to achieve this. This paper describes the technology behind Daala and discusses where it fits in the newly created AV1 codec from the Alliance for Open Media. We show that Daala is approaching the performance level of more mature, state-of-the art video codecs and can contribute to improving AV1.

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 2-D and 3-D wavelet subbands. Experiments show that the decoding speeds of the proposed coding model are four times and nine times faster than uncoded 2-D-SPIHT and 3-D-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.

Summary form only given. A very fast, low complexity algorithm for resolution-scalable and random access decoding is presented. The algorithm avoids the multiple passes of bit-plane coding for speed improvement. The decrease in dynamic range of wavelet coefficient magnitudes is efficiently coded. The hierarchical dynamic range coding naturally enables resolution-scalable representation of a wavelet transformed image. The method predicts the dynamic range of energy in each subset based on the dynamic range of energy of a parent set. Speed improvement over SPIHT is up to two times in encoding, and up to four times in decoding. The loss of quality is very small. Our method outperforms the LTW in Oliver et al. (2003), by up to two times in encoding and up to seven times in decoding.

A degree-k zero tree model is presented, in order to quantify the coding power of zerotrees in wavelet-based image coding. Based on the model, the coding behaviors of modern zerotree based image coders are clearly explained. Also, we explain why the well-known SPIHT algorithm can code a wider range of zerotrees than EZW. Experimental results support our idea that higher degree zerotree coder will have more coding power.

A very fast, low complexity algorithm for resolution scalable and random access decoding is presented. The algorithm avoids the multiple passes of bit-plane coding for speed improvement. The decrease in dynamic ranges of wavelet coefficients magnitudes is efficiently coded. The hierarchical dynamic range coding naturally enables a resolution scalable representation of a wavelet transformed image.