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In this paper we have proposed two co mparative approaches for the contrast enhancement of dark sports images. The contrast of any image is a very important characteristic wh ich decides the quality of image. Lo w contrast images occur often due to poor or non uniform lighting conditions and sometimes due to the non linearity or small dynamic range of the imaging system. Enhancing the contrast of sports images is of importance since it is difficult to analyze the performance of the team or player with a poor quality image. Though several methods are proposed for gray scale images, enhancing the contrast of color images is a comp licated process. In this paper we have proposed two comparative approaches for the contrast enhancement of color images and have compared their perfo rmance against the standard histogram equalization method. First method is contrast enhancement of color images using fuzzy rule based method and the second method is using modified sigmo id function. Color images cannot be processed directly hence a suitable color model is chosen for processing and the proposed methods are imp lemented. Fo r both the approaches the color images are split into RGB p lanes and the proposed operation is performed on each plane and finally the planes are concatenated to obtain the enhanced image. Performance of the proposed methods is measured using a factor known as Measure of Contrast and the comparison is represented graphically. Experimental results prove that of the two methods proposed, contrast enhancement using modified sigmoid function provides the highest measure of contrast and can be effectively used for further analysis of sports color images.

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