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Image Compression Algorithms – Comparative Analysis

Publication Type : Conference Proceedings

Publisher : IEEE

Source : 2025 3rd International Conference on Integrated Circuits and Communication Systems (ICICACS)

Url : https://doi.org/10.1109/icicacs65178.2025.10968818

Campus : Bengaluru

School : School of Computing

Department : Computer Science and Engineering

Year : 2025

Abstract : Due to the abundance of the new digital media data, the issue of image quality and volume of data requiring compression has become a significant factor of concern, especially in media storage and transmitting. This work affords a comparative analysis of different image compression techniques with focus on the compression ratio, quality preservation, and complexity. A new hybrid model of Predictive Coding, Run Length Coding and Quantum Entropy Coding (QEC) is proposed and shown to exhibit negligible quality loss with substantial space saving. The experimental outcomes show that the proposed method reduces space 80 percent and works better than previous methods for areas requiring high speed and relative accuracy. These insights are timely, as practical computing-communication trade-offs are paramount in the new generation of social networks, medicine, and multimedia streaming

Cite this Research Publication : G. Niharika Reddy, M. Namrutha, Namratha Akshaya, Sreebha Bhaskaran, Image Compression Algorithms - Comparative Analysis, 2025 3rd International Conference on Integrated Circuits and Communication Systems (ICICACS), IEEE, 2025, https://doi.org/10.1109/icicacs65178.2025.10968818

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