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Dictionary-based histogram packing technique for lossless image compression
This paper proposes a dictionary-based histogram packing technique for lossless image compression. It is used to improve the performance of the state-of-the-art lossless image compression standards and methods when compressing sparse and locally sparse histogram images. The proposed method leverages...
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Published in: | Journal of visual communication and image representation 2023-09, Vol.95, p.103894, Article 103894 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | This paper proposes a dictionary-based histogram packing technique for lossless image compression. It is used to improve the performance of the state-of-the-art lossless image compression standards and methods when compressing sparse and locally sparse histogram images. The proposed method leverages inter-block correlations and similarities not only within the neighborhood but also across the entire image, thereby effectively reducing the block boundary artifacts commonly observed in block-based histogram packing techniques. To achieve this, a dictionary is employed to represent highly correlated blocks using a key that captures the union of their active symbol sets. Experimental results have demonstrated that the proposed method, when applied to sparse and locally sparse histogram images, enhances the performance of various state-of-the-art lossless image compression techniques. Notably, improvements were observed in standards and methods such as JPEG-2000, JPEG-LS, JPEG-XL, PNG, and CALIC.
•Proposed a dictionary-based histogram packing technique for lossless image compression.•Improved the performance of state-of-the-art lossless image compression standards and methods for sparse and locally sparse histogram images.•Leveraged inter-block correlations and similarities across the entire image to effectively reduce block boundary artifacts.•Utilized a dictionary to represent highly correlated blocks using a key representing their active symbol sets.•Demonstrated through experiments the enhanced performance of the proposed method in various lossless image compression techniques. |
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ISSN: | 1047-3203 1095-9076 |
DOI: | 10.1016/j.jvcir.2023.103894 |