Noise induced segmentation of noisy color image

In this paper we have proposed Noise Induced HSI model based noisy and blurred colour image segmentation technique. This approach uses additive noise to suppress the effect of internal noise present in an image for proper detection of objects from such images. In this algorithm we decompose a given image in Hue, Saturation and Intensity (HSI) components and then apply processing on intensity component of the decomposed image. We measured performance of proposed algorithm in terms of correlation coefficient and number of mismatch pixels. The effectiveness of the proposed algorithm is compared with the different existing techniques. It is observed that the computational complexity of our algorithm is less in comparison with several existing techniques, because it deals only with intensity component of the decomposed image. Furthermore, an additional advantage, our technique of segmentation gives better performance as compared to SSR based segmentation using RGB model, SR-extended, integrated region matching, watershed and marker controlled watershed based segmentation method.