An adaptive gamma correction for image enhancement

Abstract

Due to the limitations of image-capturing devices or the presence of a non-ideal environment, the quality of digital images may get degraded. In spite of much advancement in imaging science, captured images do not always fulfill users' expectations of clear and soothing views. Most of the existing methods mainly focus on either global or local enhancement that might not be suitable for all types of images. These methods do not consider the nature of the image, whereas different types of degraded images may demand different types of treatments. Hence, we classify images into several classes based on the statistical information of the respective images. Afterwards, an adaptive gamma correction (AGC) is proposed to appropriately enhance the contrast of the image where the parameters of AGC are set dynamically based on the image information. Extensive experiments along with qualitative and quantitative evaluations show that the performance of AGC is better than other state-of-the-art techniques.