An optimal adaptive thresholding based sub-histogram equalization for brightness preserving image contrast enhancement
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In this paper, a new adaptive thresholding based sub-histogram equalization (ATSHE) scheme is proposed for contrast enhancement and brightness preservation with retention of basic image features. The histogram of an input image is divided into different sub-histogram using adaptive thresholding intensity values. The number of threshold values or sub-histograms of the image are not fixed, but depends on the peak signal-to-noise ratio (PSNR) of the thresholded image. Histogram clipping is also used here to control the undesired enhancement of resultant image thus avoiding over-enhancement. Median value of the original histogram gives the threshold value of clipping process. The main objective of proposed method is to improve contrast enhancement with preservation of mean brightness value, structural similarity index (SSIM) and information content of the images. Image contrast enhancement is examined by well-known enhancement assessment parameters such as contrast per pixel and modified measure of enhancement. The mean brightness preservation of the image is evaluated by using absolute mean brightness error value and feature preservation qualities are checked through SSIM and PSNR values. Through the proposed routine, the enhanced images achieve a good trade-off between features enhancement, low contrast boosting and brightness preservation in addition with the natural feel of the original image. In particular, the proposed ATSHE scheme due to its adaptive nature of threshold selection can successfully enhance images under oodles of weak illumination situations such as backlighting effects, non-uniform illumination low contrast and dark images.
KeywordsAdaptive thresholding Brightness preservation Contrast enhancement Peak signal-to-noise ratio Sub-histogram equalization Color satellite images
The authors wish to thank the editors and anonymous referees for their constructive criticism and valuable suggestions.
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