A Noise Constrained Diffusion (NC-Diffusion) Framework for High Fidelity Image Compression
With the great success of diffusion models in image generation, diffusion-based image compression is attracting increasing interests. However, due to the random noise introduced in the diffusion learning, they usually produce reconstructions with deviation from the original images, leading to suboptimal compression results. To address this problem, in this paper, we propose a Noise Constrained Diffusion (NC-Diffusion) framework for high fidelity image compression. Unlike existing diffusion-based compression methods that add random Gaussian noise and direct the noise into the image space, the proposed NC-Diffusion formulates the quantization noise originally added in the learned image comp...
| Authors | Zhenyu Du, Yanbo Gao, Shuai Li et al. |
|---|---|
| Primary category | eess.IV |
| Published | 8 April 2026 |
| Last updated at source | 8 April 2026 |
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