Contrast Restoration by Adaptive Countershading

We address the problem of communicating contrasts in images degraded with respect to their original due to processing with computer graphics algorithms. Such degradation can happen during the tone mapping of high dynamic range images, or while rendering scenes with low contrast shaders or with poor lighting. Inspired by a family of known perceptual illusions: Craik-O’Brien-Cornsweet, we enhance contrasts by modulating brightness at the edges to create countershading profiles. We generalize unsharp masking by coupling it with a multi-resolution local contrast metric to automatically create the countershading profiles from the sub-band components which are individually adjusted to each corrected feature to best enhance contrast with respect to the reference. Additionally, we employ a visual detection model to assure that our enhancements are not perceived as objectionable halo artifacts. The overall appearance of images remains mostly unchanged and the enhancement is achieved within the available dynamic range. We use our method to post-correct tone mapped images and improve images using their depth information.