English(EN) Fidelity-Constrained Anchoring for Black-Box Denoisers

新框架锚定黑盒去噪器输出以提高保真度

作者 PulseAugur 编辑部 · [1 个来源] · 2026-08-14 04:00

研究人员开发了一个名为保真度约束锚定（Fidelity-Constrained Anchoring）的新框架，旨在改进黑盒去噪器的输出。该方法将去噪后的图像与原始输入进行混合，并应用一个符合特定局部保真度约束（如峰值信噪比（PSNR）或结构相似性指数（SSIM））的混合因子。在DIV2K数据集上的实验表明，这种锚定策略在保持去噪性能和统计自然度之间取得平衡的同时，能有效控制保真度。 AI

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arXiv cs.CV TIER_1 English(EN) · Masaki Satoh · 2026-08-14 04:00

面向黑盒去噪器的保真度约束锚定

arXiv:2608.13194v1 Announce Type: new Abstract: We propose a fidelity-constrained framework that anchors the output of a black-box denoiser to its input without retraining and with little additional computation. The method linearly blends the denoised image with the input and sel…

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面向黑盒去噪器的保真度约束锚定

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