Refining Coded Image in Human Vision Layer Using CNN-Based Post-Processing

Takahiro Shindo; Yui Tatsumi; Taiju Watanabe; Hiroshi Watanabe

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arXiv · 2405.11894

Refining Coded Image in Human Vision Layer Using CNN-Based Post-Processing

Takahiro Shindo·Yui Tatsumi·Taiju Watanabe·Hiroshi Watanabe

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Abstract

Scalable image coding for both humans and machines is a technique that has gained a lot of attention recently. This technology enables the hierarchical decoding of images for human vision and image recognition models. It is a highly effective method when images need to serve both purposes. However, no research has yet incorporated the post-processing commonly used in popular image compression schemes into scalable image coding method for humans and machines. In this paper, we propose a method to enhance the quality of decoded images for humans by integrating post-processing into scalable coding scheme. Experimental results show that the post-processing improves compression performance. Furthermore, the effectiveness of the proposed method is validated through comparisons with traditional methods.

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Takahiro Shindo, Yui Tatsumi, Taiju Watanabe, Hiroshi Watanabe. 2024-05-20. Refining Coded Image in Human Vision Layer Using CNN-Based Post-Processing. https://arxiv.org/abs/2405.11894

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