Image sub-division and quadruple clipped adaptive histogram equalization (ISQCAHE) for low exposure image enhancement

• Published in: Multidimensional systems and signal processing Vol. 34; no. 1; pp. 25 - 45
• Main Authors: Acharya, Upendra Kumar, Kumar, Sandeep
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.03.2023; Springer Nature B.V
• Subjects: Artificial Intelligence; Brightness; Circuits and Systems; Electrical Engineering; Engineering; Entropy; Equalization; Exposure; Histograms; Image enhancement; Image quality; Probability density functions; Quality assessment; Signal,Image and Speech Processing; Similarity; Histogram sub-division; Histogram clipping; Low exposure images; Image enhancement; Histogram equalization (HE)
• ISSN: 0923-6082; 1573-0824
• DOI: 10.1007/s11045-022-00853-9

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.