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WISE: A Framework for Gigapixel Whole-Slide-Image Lossless Compression

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arxiv 2503.18074 v1 pith:NRYLDJNU submitted 2025-03-23 eess.IV cs.CV

classification eess.IVcs.CV
keywords imageswisecompressionlosslessanalysiscompresseffectiveeffectively
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Whole-Slide Images (WSIs) have revolutionized medical analysis by presenting high-resolution images of the whole tissue slide. Despite avoiding the physical storage of the slides, WSIs require considerable data volume, which makes the storage and maintenance of WSI records costly and unsustainable. To this end, this work presents the first investigation of lossless compression of WSI images. Interestingly, we find that most existing compression methods fail to compress the WSI images effectively. Furthermore, our analysis reveals that the failure of existing compressors is mainly due to information irregularity in WSI images. To resolve this issue, we developed a simple yet effective lossless compressor called WISE, specifically designed for WSI images. WISE employs a hierarchical encoding strategy to extract effective bits, reducing the entropy of the image and then adopting a dictionary-based method to handle the irregular frequency patterns. Through extensive experiments, we show that WISE can effectively compress the gigapixel WSI images to 36 times on average and up to 136 times.

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  1. EDPC: Accelerating Lossless Compression via Lightweight Probability Models and Decoupled Parallel Dataflow

    cs.IT 2025-07 conditional novelty 4.0 of 10

    EDPC reports state-of-the-art lossless compression ratios across text, image, float, and benchmark datasets while running about 2.7x faster than the strongest prior learned compressor, PAC.

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