An improved symbol reduction technique based Huffman coder for efficient entropy coding in the transform coders. Issue 4 (26th December 2020)

• Record Type: Journal Article
• Authors: Thakur, Vikrant Singh; Thakur, Kavita; Gupta, Shubhrata
• Is Part Of: IET image processing. Volume 15:Issue 4(2021)
• Page Start: 1008
• Page End: 1022
• Publication Date: 2020-12-26
• Subjects: Image processing -- Periodicals; 621.36705
• DOI: 10.1049/ipr2.12081
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract: Entropy coding is the essential block of transform coders that losslessly converts the quantized transform coefficients into the bit‐stream suitable for transmission or storage. Usually, the entropy coders exhibit less compression capability than the lossy coding techniques. Hence, in the past decade, several efforts have been made to improve the compression capability of the entropy coding technique. Recently, a symbol reduction technique (SRT) based Huffman coder is developed to achieve higher compression than the existing entropy coders at similar complexity of the regular Huffman coder. However, the SRT‐based Huffman coding is not popular for the real‐time applications due to the improper negative symbol handling and the additional indexing issues, which restrict its compression gain at most 10–20% over the regular Huffman coder. Hence, in this paper, an improved SRT (ISRT) based Huffman coder is proposed to properly alleviate the deficiencies of the recent SRT‐based Huffman coder and to achieve higher compression gains. The proposed entropy coder is extensively evaluated on the ground of compression gain and the time complexity. The results show that the proposed ISRT‐based Huffman coder provides significant compression gain against the existing entropy coders with lower time consumptions.