Image Compression Algorithms - Comparative Analysis

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 fo...

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Veröffentlicht in:2025 3rd International Conference on Integrated Circuits and Communication Systems (ICICACS) S. 1 - 7
Hauptverfasser: Niharika Reddy, G., Namrutha, M., Akshaya, Namratha, Bhaskaran, Sreebha
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 21.02.2025
Schlagworte:
Entropy coding
Image coding
Image compression
Image quality
Integrated circuits
Media
Prediction algorithms
Predictive coding
Predictive models
Quantum Entropy Coding (QEC)
Run-Length Coding
Social networking (online)
Streaming media
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Zusammenfassung: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.
DOI:10.1109/ICICACS65178.2025.10968818