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Alternative polyadenylation (APA) is observed in virtually all metazoans and results in mRNA isoforms with different 3’ends. It is routinely...

This paper investigates various classification techniques, applied to subband coding of images, as a way of exploiting the nonstationary nature of image subbands. The advantages of subband classification are characterized in a rate-distortion framework in terms of "classification gain" and overall "subband classification gain." Two algorithms, maximum classification gain and equal mean-normalized standard deviation classification, which allow unequal number of blocks in each class, are presented. The dependence between the classification maps from different subbands is exploited either directly while encoding the classification maps or indirectly by constraining the classification maps. The trade-off between the classification gain and the amount of side information is explored. Coding results for a subband image coder based on classification are presented. The simulation results demonstrate the value of classification in subband coding.

A Screen Content coding (SCC) extension to High Efficiency Video Coding (HEVC) is currently under development by the Joint Collaborative Team on Video Coding (JCT-VC), which is a joint effort from the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group. The main goal of the HEVC screen content coding standardization effort is to enable significantly improved compression performance for videos containing a substantial amount of still or moving rendered graphics, text, and animation rather than, or in addition to, camera-captured content. This paper provides an overview of the technical features and characteristics of the current HEVCSCC test model and related coding tools, including intra block copy, palette mode, adaptive colour transform, and adaptive motion vector resolution. The performance of the screen content coding extension is compared against existing standards in terms of bit-rate savings at equal distortion. IEEE Transactions on Circuits and Systems for Video TechnologyThis work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved.Abstract-A Screen Content coding (SCC) extension to High Efficiency Video Coding (HEVC) is currently under development by the Joint Collaborative Team on Video Coding (JCT-VC), which is a joint effort from the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group. The main goal of the HEVC screen content coding standardization effort is to enable significantly improved compression performance for videos containing a substantial amount of still or moving rendered graphics, text, and animation rather than, or in addition to, camera-captured content. This paper provides an overview of the technical features and characteristics of the current HEVC-SCC test model and related coding tools, including intra block copy, palette mode, adaptive colour transform, and adaptive motion vector resolution. The performance of the screen content coding extension is compared against existing standards in terms of bit-rate savings at equal distortion.

Abstract-This paper describes transform coefficient coding in the draft international standard of High Efficiency Video Coding (HEVC) specification and the driving motivations behind its design. Transform coefficient coding in HEVC encompasses the scanning patterns and coding methods for the last significant coefficient, significance map, coefficient levels, and sign data. Special attention is paid to the new methods of last significant coefficient coding, multilevel significance maps, high-throughput binarization, and sign data hiding. Experimental results are provided to evaluate the performance of transform coefficient coding in HEVC.Index Terms-High Efficiency Video Coding (HEVC), high throughput entropy coder, transform coefficient coding, video coding.

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