Abstract
JPEG images are widely used by individual users, data centers, cloud storages, and network file systems. The huge transmission and storage bandwidth of existing JPEG images is becoming a big challenge due to its low compression efficiency. Some methods such as Google’s Brunsli can further compress these JPEG images adequately and restore them back to JPEG format losslessly when needed, but its decoding speed is not fast enough especially for real-time mobile applications. To further reduce its decoding complexity, we proposed three optimizations based on Brunsli, which include using asymmetric numeral systems coding to replace the existing arithmetic coding, designing the joint encoding of multiple symbols and cache-friendly optimizing the data structures. Experimental results demonstrate that compared with Brunsli, the proposed method achieves average 1.86–2.25 times decoding faster on mobile platform with comparable compression efficiency which is really valuable for power sensitive real-time mobile applications.
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All data included in this study are available upon request by contact with the corresponding author. The source code is not publicly available due to privacy.
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QS: Conceptualization, Methodology. HZ: Software, Data curation, Writing-Original draft preparation. HS: Software Validation. CL: Software, Methodology Writing - Review & Editing. All authors reviewed the manuscript.
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Sheng, Q., Zhu, H., Sheng, H. et al. High efficiency lossless image recompression algorithm with asymmetric numeral systems for real-time mobile application. J Real-Time Image Proc 20, 90 (2023). https://doi.org/10.1007/s11554-023-01346-z
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DOI: https://doi.org/10.1007/s11554-023-01346-z