Training-Free Continuous Bitrate Control for Scalable Image Coding for Humans and Machines
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866914619473264640 |
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| author | Tatsumi, Yui Watanabe, Hiroshi |
| author_facet | Tatsumi, Yui Watanabe, Hiroshi |
| contents | Continuous variable-rate compression is highly demanded in real-world applications, but remains underexplored in scalable image coding for humans and machines. In this paper, we propose a training-free variable-rate scalable image coding framework. By adjusting quantization steps based on predicted scale values, the proposed method achieves continuous bitrate control while preserving high-scale information in the machine and enhancement layers. Experimental results demonstrate the effectiveness of the proposed method and highlight the importance of bitrate allocation between the two layers. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2606_00158 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Training-Free Continuous Bitrate Control for Scalable Image Coding for Humans and Machines Tatsumi, Yui Watanabe, Hiroshi Image and Video Processing Computer Vision and Pattern Recognition Continuous variable-rate compression is highly demanded in real-world applications, but remains underexplored in scalable image coding for humans and machines. In this paper, we propose a training-free variable-rate scalable image coding framework. By adjusting quantization steps based on predicted scale values, the proposed method achieves continuous bitrate control while preserving high-scale information in the machine and enhancement layers. Experimental results demonstrate the effectiveness of the proposed method and highlight the importance of bitrate allocation between the two layers. |
| title | Training-Free Continuous Bitrate Control for Scalable Image Coding for Humans and Machines |
| topic | Image and Video Processing Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2606.00158 |