Abstract
Conventional contrast enhancement techniques often fail to produce satisfactory results for low-contrast images, and cannot be automatically applied to different images because their processing parameters must be specified manually to produce a satisfactory result for a given image. This work presents a colour-preserving contrast enhancement (CPCE) algorithm for images. Modification to images was performed in the HSV colour-space. The Hue component is preserved (unchanged), luminance modified using Contrast Limited Adaptive Histogram Equalization (CLAHE), while Saturation components were up-scaled using a derived mapping function on the approximate components of its discrete wavelet transform. Implementation was done in MATLAB and compared with CLAHE and Histogram Equalization (HE) algorithms in the RGB colour space. Subjective (visual quality inspection) and objective parameters (Peak-signal-to-noise ratio (PSNR), Absolute Mean Brightness Error (AMBE) and Mean squared error (MSE)) were used for performance evaluation. The method produced images with the lowest MSE, AMBE, and highest PSNR when tested, yet preserved the visual quality of the image.
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Ojo, J.A., Solomon, I.D., Adeniran, S.A. (2016). Colour-Preserving Contrast Enhancement Algorithm for Images. In: Chen, L., Kapoor, S., Bhatia, R. (eds) Emerging Trends and Advanced Technologies for Computational Intelligence. Studies in Computational Intelligence, vol 647. Springer, Cham. https://doi.org/10.1007/978-3-319-33353-3_11
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