2016/05/17 by Fatih Kamışlı, Fatih Kamisli · 1 citation
Computer Science · Mathematics · #Advanced Data Compression Techniques #Advanced Image Processing Techniques #Advanced Vision and Imaging #Algorithm #Arithmetic coding #Artificial intelligence #Coding (social sciences) #Computer science #Context-adaptive binary arithmetic coding #Context-adaptive variable-length coding #Data compression #Discrete cosine transform #Entropy encoding #Lossless compression #Lossy compression #Mathematics #Residual #Statistics #Theoretical computer science #Transform coding #Tunstall coding #Video Coding and Compression Technologies #cs.MM
paper · pdf · doi:10.1109/mmsp.2016.7813364
published in OpenMETU (Middle East Technical University) 13, 1-6 (Middle East Technical University)
arxiv created 2016/05/17 · openalex created_date 2016/06/24 · openalex publication_date 2016/09/01 · arxiv updated 2022/03/21 · openalex updated_date 2026/08/05
Many approaches have been proposed to support lossless coding within video coding standards that are primarily designed for lossy coding. The simplest approach is to just skip transform and quantization and directly entropy code the prediction residual, which is used in HEVC version 1. However, this simple approach is inefficient for compression. More efficient approaches include processing the residual with DPCM prior to entropy coding. This paper explores an alternative approach based on processing the residual with integer-to-integer (i2i) transforms. I2i transforms map integers to integers, however, unlike the integer transforms used in HEVC for lossy coding, they do not increase the dynamic range at the output and can be used in lossless coding. Experiments with the HEVC reference software show competitive results.