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- Title
H.264 Video Compression Using Novel Refined Huffman Codes for Omnipresent Applications.
- Authors
Kavitha, T.; Sankar, K. Jaya
- Abstract
The technologies like cloud computing, big data, data mining applications deal with large volumes of data in the form of videos, images, audio and multi-media data. To efficiently store and transmit huge volumes of data is a challenge. The data compression addresses the problem of efficient storing and transmitting of data. The need for an efficient compression technique which can encode, decode and reconstruct the data with better coding efficiency and improved Peak-Signal-to-Noise-Ratio (PSNR) is always in demand. In this research work, compression of video is considered to achieve higher Compression Ratio and reduce the effective overheads involved in coding. The research work is compared to the state-of-the-art existing H.264 video Compression technique. The H.264 video standard uses standard Huffman tables to encode the DCT transform coefficients. The proposed methodology adopts quantization followed by entropy coding with Refined Huffman (RH) codes which replaces the existing standard Huffman tables used for entropy coding. The performance parameters like Peak-Signal to Noise-Ratio (PSNR), Compression Ratio (CR) and Structural Similarity Index (SSIM) are evaluated to test the performance of the proposed RH codes. The proposed RH method attains improved PSNR of 8.4%, 1.3% improvement in SSIM and CR improvement of 2.76% compared to the existing MPEG compression. The experimental results using Refined Huffman codes performed well compared to the existing Standard Huffman tables.
- Subjects
HUFFMAN codes; VIDEO compression; DATA compression; IMAGE compression; DATA mining; CLOUD computing; BIG data
- Publication
Wireless Personal Communications, 2023, Vol 131, Issue 4, p2949
- ISSN
0929-6212
- Publication type
Article
- DOI
10.1007/s11277-023-10590-2