Abstract
Low contrast image is one of the major challenges in photography. The low contrast image not only poses difficulty to the interpretation of the scene but also causes trouble in the onward processing of the image for computer vision tasks. Histogram equalization (HE) is a traditional and widely used approach for contrast enhancement and applies to almost all types of images. However, HE causes over-enhancement of the image which degrades its natural appearance. In this paper, a novel scheme for enhancing the image contrast while retaining its naturalness has been proposed. The proposed method uses the compensated histogram equalization technique on each channel individually followed by blending of the channels with a suitable adaptive brightness adjustment kernel. The three color channels are combined to form the intermediate image. The high-frequency noise introduced during the process is filtered out. Finally, adaptive power law transformation is applied to adjust the overall brightness and to retain its naturalness. This makes the method strong in terms of contrast enhancement along with details preservation. The proposed method is applicable to all the contrast degraded images as it automatically adjusts its parameters based on the degradation level. The simulation results, on the CSIQ dataset, show that the proposed method performs better, qualitatively, and quantitatively than the existing methods.
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Kumar, A., Bhandari, A.K. & Kumar, R. 3D color channel based adaptive contrast enhancement using compensated histogram system. Multimedia Systems 27, 563–580 (2021). https://doi.org/10.1007/s00530-021-00757-x
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DOI: https://doi.org/10.1007/s00530-021-00757-x