Fidelity-Constrained Anchoring for Black-Box Denoisers
- Published
- Source
- arXiv
- Paper number
- 900
- Field
- Computer Vision
- arXiv ID
- 2608.13194
Key points
- It linearly mixes black-box denoising outputs with the input patch by patch to find the largest mixing coefficient that satisfies a target fidelity.
- It solves PSNR constraints in closed form and efficiently computes SSIM constraints through four root-finding operations using properties of inverse SSIM.
- It verified that target PSNR or SSIM can be controlled without retraining for Real-ESRGAN and a non-local means denoiser.
- SSIM-based anchoring showed a more consistent quality-naturalness trade-off than PSNR-based anchoring across three Gaussian-noise levels, making it useful as practical postprocessing.
- Because it relies on linear mixing, performance degrades when the denoised output differs substantially from the input or when noise is strong enough to damage the original structure.
Paper links
External research summaries. These are not HDATF publications or measured product results.