Color and Frequency Correction for Image Colorization
This work addresses color and frequency correction for image colorization, but it is incremental as it builds on the existing DDColor model.
The authors tackled limitations in the DDColor image colorization model, specifically frequency band issues and color cast, by constructing and combining two optimization schemes, resulting in improved performance metrics like PSNR and SSIM.
The project has carried out the re-optimization of image coloring in accordance with the existing Autocolorization direction model DDColor. For the experiments on the existing weights of DDColor, we found that it has limitations in some frequency bands and the color cast problem caused by insufficient input dimension. We construct two optimization schemes and combine them, which achieves the performance improvement of indicators such as PSNR and SSIM of the images after DDColor.