Abstract
In this article, we propose a fast and effective method for digital image contrast enhancement. The gray-level dynamic range of contrast-distorted images is extended maximally via adaptive pixel value stretching. The quantity of saturated pixels is set intelligently according to the perceptual brightness of global images. Adaptive gamma correction is also novelly used to recover the normal luminance in enhancing dimmed images. Different from prior methods, our proposed technique could be enforced automatically without complex manual parameter adjustment per image. Both qualitative and quantitative performance evaluation results show that, comparing with some recent influential contrast enhancement techniques, our proposed method achieves comparative or better enhancement quality at a surprisingly lower computational cost. Besides general computer applications, such merit should also be valuable in low-power scenarios, such as the imaging pipelines used in small mobile terminals and visual sensor network.
Highlights
Contrast enhancement (CE) refers to a type of image manipulation which could improve the perceived contrast of an image
We propose a fast and effective image CE technique, which relies on the integration of both adaptive pixel value stretching and adaptive gamma correction
BSD500 includes 500 natural images with the resolution of 321 3 481 pixels. Both classical and state-of-the-art CE algorithms including Histogram equalization (HE),[1] histogram modification (HM),4 adaptive gamma correction with weighting distribution (AGCWD),[5] ADJ,[11] and SECE7 are compared in performance evaluation
Summary
Contrast enhancement (CE) refers to a type of image manipulation which could improve the perceived contrast of an image. Keywords Image processing, contrast enhancement, fast, pixel value stretching, adaptive gamma correction
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