Expeditious Contrast Enhancement for Grayscale Images Using a New Swift Algorithm
AbstractContrast enhancement plays a significant role in many existing image-related applications. In various situations, conventional contrast enhancement techniques failed to produce acceptable results for a wide variety of low-contrast images. As a result, various innovative techniques have been proposed for the purpose of contrast enhancement. Despite that, this field is still open for research due to its indispensability in many scientific disciplines and to various unavoidable real-world limitations. Hence, this article introduces a novel swift algorithm for contrast enhancement in images of low-contrast. The processing concept of this algorithm is straightforward. Initially, a non-complex logarithmic function is applied as a preprocessing step to attenuate the immoderate pixel values. Then, a new non-linear enhancement function which is designed experimentally based on mathematical, statistical and spatial information is applied to modify the brightness and contrast. Finally, a regularization function is applied as a post-processing step to rearrange the image pixels into their natural dynamic range. Experimental results revealed the favorability of the proposed algorithm, as it provided better results than those produced by several contemporary techniques in terms of recorded accuracy and perceived quality.
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