Authors: Christian D. Rask, Daniel E. Lucani

Published on: February 07, 2024

Impact Score: 8.15

Arxiv code: Arxiv:2402.05974

Summary

• What is new: Introduction of RAGE, a new image compression framework combining efficient compression, fast decompression, pixel-level granularity in random access, and support for both lossless and lossy compression using generalized deduplication.
• Why this is important: Existing image compression techniques often fail to simultaneously provide high compression ratios, efficient decompression, and fast random access for both lossless and lossy images.
• What the research proposes: RAGE utilizes generalized deduplication to achieve high compression ratios, fast decompression, and pixel-level random access, supporting both lossless and lossy compression formats.
• Results: RAGE delivers similar or better compression ratios compared to current lossless image compressors and outperforms JPEG in lossy compression for embedded graphics, with competitive performance for natural images.

Technical Details

Technological frameworks used: Generalized Deduplication (GD)

Models used: RAGE for lossless compression, RAGE-Q for lossy compression

Data used: Nine datasets including graphics, logos, natural images

Potential Impact

Digital imaging, cloud storage providers, mobile and web applications requiring efficient image storage and retrieval, and compression software developers could benefit or need reevaluation.

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