Image Restoration Comparison

Sources, credits and test scope

Back to the comparison

Saved results from an independent proof of concept on October 22, 2026. The photograph, oil painting and abstract painting were cropped to 2048 × 2048 pixels from the distributed JPEGs without upscaling. The watercolor uses an existing 1254 × 1254 test image. These are not claimed to be lossless scans of the original works.

Methods compared

Findings and limitations

JPEG artifacts were partly reduced, but the criteria for automatic acceptance with faithful preservation of fine hairs, individual brushstrokes and signatures were not met. Sufficient banding removal was not demonstrated for WaveMamba under these synthetic quantization conditions.

JPEG Q10/20/40/60 are synthetic recompressions with 4:2:0 subsampling. RGB5/RGB4 are synthetic quantization without dithering. Clean controls were also processed. There is one source image per material type. This does not measure performance on customer images, print proofs, artist acceptance, unknown-quality estimation, labor savings or a general success rate. The original was not supplied as an additional model reference or used for output post-processing; clean controls use the unchanged original as their declared input.

Auxiliary metrics were calculated on saved RGB8 pixels in native coordinates. LPIPS uses the AlexNet 0.1 family on limited regions and does not establish the correctness of signatures or individual brushstrokes. APSNR and DBI were not measured. Passing metric and software checks does not establish acceptable visual quality.

The English and Japanese pages share identical image files and metric values. Saved PNG sheets retain their Japanese headers. Their columns, from left to right, are Original / Degraded input (or clean control) / Restoration output. Full views are reduced display previews; detail views use native 100% or nearest-neighbor 200% display.

This repository contains only static HTML, images and public comparison records. It excludes inference code, weights, environments and internal logs. It does not grant a blanket license covering all images or pretrained models.