Algoritma-algoritma pembetulan warna baharu untuk imej digital berwarna
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Date
2016-04-01
Authors
Mohd Naim Mohd Jain Noordin
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Abstract
Color correction algorithm for digital color image is important to reduce the impact of inhomogeneous surrounding illumination in digital color image. Color correction algorithm is divided into two main processes, namely the surrounding illumination color estimation process and color correction process. Although there are various color correction algorithms introduced, the resultant images produced are still prone to the effect of saturated and over-corrected phenomenon. To overcome the drawback of these conventional algorithms, three new color correction algorithms were introduced namely Pixel Distribution Color Correction (PDCC), Saturation Avoidance Color Correction (SACC) and Adaptive Color Correction (ACC). The proposed algorithms apply the color correction processes by shifting the pixel distribution based on the 2D two color channel plane. From the qualitative analysis results, the PDCC algorithm was able to produce the best resultant image for indoor images. The produced human skin color looks more natural and more pleasantly in viewing. The SACC algorithm which employs the saturation limitation algorithm was found to be suitable to correct the over-exposed area on the image. The ACC algorithm on the other hand is the most suitable algorithm to be used to correct the color of underwater images with effect of minimal saturation phenomenon as compared to other conventional color correction algorithm. The results of quantitative analysis showed that all the proposed three color correction algorithms not only have the ability to correct the colors of the images, but also are able to preserve the brightness of the image, enhance the image details, increase naturalness
index, and increase the contrast of the image. A new quantitative analysis namely Saturation Pixel Detection Analysis (SPDA) is also introduced in this research. The SPDA analysis successfully detects the saturated and over-corrected pixel more accurately and unbiased. The result produced by SPDA can be correlated and coherent with the qualitative analysis carried out.