Automatic Detection and Correction for Glossy Reflections in Digital Photograph

[[abstract]]The popularization of digital technology has made shooting digital photos and using related applications a part of daily life. However, the use of flash, to compensate for low atmospheric lighting, often leads to overexposure or glossy reflections. This study proposes an auto-detection and inpainting technique to correct overexposed faces in digital photography. This algorithm segments the skin color in the photo as well as uses face detection and capturing to determine candidate bright spots on the face. Based on the statistical analysis of color brightness and filtering, the bright spots are identified. Finally, bright spots are corrected through inpainting technology. From the experimental results, this study demonstrates the high accuracy and efficiency of the method

Multilayer Inpainting on Digitalized Artworks

[[abstract]]Image inpainting automatically restores damaged images and partially removed pictures. Since most inpainting mechanisms inpaint damaged portions in a single layer, this study proposes a multilayer inpainting mechanism by examining how Chinese paintings are drawn in layers. The proposed multilayer inpainting mechanism employs a layer fusion strategy to detect the optimal inpaint combination among layers to restore paintings. Because this multilayer multi-resolution strategy considers damages in each layer from a multi-resolution perspective, it is superior to several existing techniques for restoring Chinese and Western paintings. In this study, the proposed algorithm is tested on more than 1,500 still images, with evaluations showing the effectiveness of image inpainting.The results indicate that the proposed algorithm achieves high PSNR values as well as high user satisfactions, including inpainting in some extreme cases where more than ninety percent of a painting are destroyed

Multilayer Inpainting on Digitalized Artworks

[[abstract]]Image inpainting automatically restores damaged images and partially removed pictures. Since most inpainting mechanisms inpaint damaged portions in a single layer, this study proposes a multilayer inpainting mechanism by examining how Chinese paintings are drawn in layers. The proposed multilayer inpainting mechanism employs a layer fusion strategy to detect the optimal inpaint combination among layers to restore paintings. Because this multilayer multi-resolution strategy considers damages in each layer from a multi-resolution perspective, it is superior to several existing techniques for restoring Chinese and Western paintings. In this study, the proposed algorithm is tested on more than 1,500 still images, with evaluations showing the effectiveness of image inpainting. The results indicate that the proposed algorithm achieves high PSNR values as well as high user satisfactions, including inpainting in some extreme cases where more than ninety percent of a painting are destroyed