In this paper, a novel image sub-division and quadruple clipped adaptive histogram equalization (ISQCAHE) technique is proposed for the enhancement of low exposure images. The proposed method involves, computation of the histogram which includes a new approach of image sub-division, enhancement controlling mechanism, modification of probability density function (PDF) and histogram equalization (HE). The original histogram is segmented into sub-histograms based on exposure threshold and mean, to preserve the brightness and entropy. Then, individual sub-histogram is clipped separately to control the enhancement rate. For enhancing the visual quality, HE is applied to individual sub-histogram using the modified PDF. The experimental results show that, the proposed ISQCAHE method avoids the unpleasant artifacts effectively and provide a natural appearance to the enhanced image. It is simple, adaptive and performs superior than other techniques in terms of visual quality, absolute mean brightness error, entropy, Natural image quality evaluation, brightness preservation, structure similarity index measure and feature similarity index measure.
Keywords: Histogram clipping; Histogram equalization (HE); Histogram sub-division; Image enhancement; Low exposure images.
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.