Benchmarking Denoising Algorithms with Real Photographs

Understand

Lacking realistic ground truth data, image denoising techniques are traditionally evaluated on images corrupted by synthesized i.i.d.

• Gaussian noise.
• We aim to obviate this unrealistic setting by developing a methodology for benchmarking denoising techniques on real photographs.
• We capture pairs of images with different ISO values and appropriately adjusted exposure times, where the nearly noise-free low-ISO image serves as reference.