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Establishment of an Efficient Color Model from Existing Models for Better Gamma Encoding In Image Processing
T. M. Shahriar Sazzad, Sabrin Islam, Mohammad Mahbubur Rahman Khan Mamun, Md. Zahid Hasan
Pages - 90 - 100     |    Revised - 15-01-2013     |    Published - 28-02-2013
Volume - 7   Issue - 1    |    Publication Date - February 2013  Table of Contents
Gamma, Human vision, RGB, HSI, HSB, Light.
Human vision is an important factor in the areas of image processing. Research has been done for years to make automatic image processing but still human intervention can not be denied and thus better human intervention is necessary. Two most important points are required to improve human vision which are light and color. Gamma encoder is the one which helps to improve the properties of human vision and thus to maintain visual quality gamma encoding is necessary.

It is to mention that all through the computer graphics RGB (Red, Green, and Blue) color space is vastly used. Moreover, for computer graphics RGB color space is called the most established choice to acquire desired color. RGB color space has a great effort on simplifying the design and architecture of a system. However, RGB struggles to deal efficiently for the images those belong to the real-world.

Images are captured using cameras, videos and other devices using different magnifications. In most cases during processing, in compare to the original outlook the images appear either dark or bright in contrast. Human vision affects and thus poor quality image analysis may occur. Consequently this poor manual image analysis may have huge difference from the computational image analysis outcome. Question may arise here why we will use gamma encoding when histogram equalization or histogram normalization can enhance images. Enhancing images does not improve human visualization quality all the time because sometimes it brightens the image quality when it is needed to darken and vice-versa. Human vision reflects under universal illumination environment (not pitch black or blindingly bright) thus follows an approximate gamma or power function. Hence, this is not a good idea to brighten images all the time when better human visualization can be obtained while darkening the images. Better human visualization is important for manual image processing which leads to compare the outcome with the semiautomated or automated one. Considering the importance of gamma encoding in image processing we propose an efficient color model which will help to improve visual quality for manual processing as well as will lead analyzers to analyze images automatically for comparison and testing purpose.
CITED BY (5)  
1 Sazzad, T. M., Armstrong, L. J., & Tripathy, A. K. (2015, November). An Automated Detection Process to Detect Ovarian Tissues Using Type P63 Digitized Color Images. In Tools with Artificial Intelligence (ICTAI), 2015 IEEE 27th International Conference on (pp. 278-285). IEEE.
2 Thu, T. T. H., Lan, P. T., & Ai, T. T. H. (2013). Rule set of object-oriented classification using Landsat imagery in Donganh, Hanoi, Vietnam. ???????, 31(6-2), 521-527.
3 Sazzad, T. S., & Islam, S. Use of gamma encoder on HSL color model improves human visualization in the field of image processing. Issues, 1(1), 177-182.
4 Sazzad, T. S., & Islam, S. Automatic detection of human body parts especially human hands considering gamma correction and template matching on noisy images. IJENS [International Journal of Engineering Research and Applications], ISSN, 2077-1207.
5 Sajati, H., & Astuti, Y. analisis dan perancangan software untuk menentukan warna kendaraan gelap dan terang.
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Mr. T. M. Shahriar Sazzad
Department of Computer Science University of St Andrews St Andrews - United Kingdom
Mr. Sabrin Islam
Department of Computer Science American International University Bangladesh Dhaka - Bangladesh
Mr. Mohammad Mahbubur Rahman Khan Mamun
EEE, BUET Dhaka - Bangladesh
Mr. Md. Zahid Hasan
Lecturer, Dept. of CSE Green University Dhaka - Bangladesh