Controllable Image Illumination Enhancement with an Over-Enhancement Measure
Chen Bai, Amy R. Reibman · 2018
The quality of images or videos that suffer from exposure distortions can be enhanced using histogram equalization or retinex methods. However, the relationship between the visual quality and the degree of enhancement is an inverted U-shaped function with a peak point, and many existing methods have parameters that have no clear relationship with image quality. We introduce a controllable illumination enhancement system, where the degree of enhancement can be adjusted using a single parameter. We then propose an over-enhancement measure, Lightness Order Measure (LOM), which quantifies the unnaturalness based on a local inversion of lightness order. We explore the relationship between the peak point and LOM in a subjective test. The results indicate that LOM reduces content dependency compared to existing methods. Our subjective test also evaluates the image quality of our enhancement, and demonstrates the effectiveness of our method.