Adaptive Chroma Correction of Tone Mapping Operators for Natural Image Appearance

Preserving perceptual quality of the tone mapped images is one of the major challenges in tone mapping. Most traditional tone mapping operators (TMOs) compress the luminance of high dynamic range (HDR) images without taking account of image color information, resulting into less natural or preferable colors. Current color management algorithms require either manual fine-tuning or introduce lightness and hue shifts. An adaptive color correction model is proposed to address color distortions in tone mapping. It is based on the CIECAM16 to compute perceptual correlates, i.e., Lightness, Chroma and Hue. Regardless of the tone mapping technique, the proposed model recovers natural colors of tone mapped images for spatially invariant and variant operators, making it an effective postprocessing technique for color reproduction. Unlike other models, it requires no gamut mapping correction, reproducing more accurate hue, chroma, and lightness. The algorithm was evaluated using objective and subjective methods, revealing that it produced significantly better color reproduction for tone mapped images in terms of naturalness of the colors.