Abstract
Dark Channel Prior (DCP) is originally introduced to remove the haze effects from a digital image. Though the effectiveness of the DCP approach on haze removal, the DCP approach often leads the recovered image to become darker even though the haze effects had been removed. The images with the same or similar levels of color mean are likely without the problem of color shifts. Therefore, we have created a color mean adjustment method to adjust for the color shift by balancing the means of the color channels. CLAHE is employed in this study to boost the image’s contrast, while the color mean adjustment method is utilized to smooth its final appearance. Throughout the experiments like visual comparison analysis, Peak Signal-to-Noise Ratio (PSNR), and Universal Quality Index (UQI), our proposed method proved to be a highly effective post-processing approach for the DCP approach as it suppresses more image noises, enhance image quality, and, more importantly, allows the DCP approach to be used on underwater images. Besides, our proposed method also resolves the dark look issue of the DCP approach.
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Yao, D.N.L., Bade, A., Zolkifly, I.A., Daud, P. (2023). A Naive but Effective Post-processing Approach for Dark Channel Prior (DCP). In: Wah, Y.B., Berry, M.W., Mohamed, A., Al-Jumeily, D. (eds) Data Science and Emerging Technologies. DaSET 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 165. Springer, Singapore. https://doi.org/10.1007/978-981-99-0741-0_5
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DOI: https://doi.org/10.1007/978-981-99-0741-0_5
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