Image quality enhancement support system by gamma correction using interactive evolutionary computation

By noting gamma correction as one of the image quality adjustment parameters, the authors create an image quality enhancement support system capable of reflecting user subjectivity. In this study, the derivation of an optimum gamma value is formulated as an optimization problem. To reflect user subjectivity, an image quality enhancement support system is realized by interactive evolutionary computation. This technique is verified by comparing it with a manually derived gamma value, image quality, and derivation time.