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Volume : III, Issue : IX, October - 2013 IMAGE QUALITY PARAMETERS FOR THE ANALYSIS OF SEGMENTATION OF SATELLITE IMAGES IN TWO DIFFERENT COLOR SPACES GANESAN P AND V.RAJINI DOI : 10.9780/22307850, Published By : Laxmi Book Publication Abstract : Image quality parameters are the figure of merit widely used in the image processing applications to analyze and compare the output image with the input image. These measures are widely used in image compression, segmentation, feature extraction, object detection and tracking, and image based measurements. In this paper, these parameters measure the similarity or dissimilarity between the two images on the basis of comparing the corresponding pixels of the two images and present a numerical value as a result. The segmentation is one of the most challenging and important process in the image analysis. The success of the image analysis is based on the result produced in the segmentation stage. This paper presents a comparative study of the segmentation of high resolution satellite images in RGB and HSV color spaces using modified k-means clustering algorithm. The segmented images are compared with the original input images by using number of bivariate image quality parameters. To test the efficiency and robustness of the proposed method, the experiments are performed on GeoEye-1 satellite images. Keywords : Article : Cite This Article : GANESAN P AND V.RAJINI , (2013). IMAGE QUALITY PARAMETERS FOR THE ANALYSIS OF SEGMENTATION OF SATELLITE IMAGES IN TWO DIFFERENT COLOR SPACES. Indian Streams Research Journal, Vol. III, Issue. IX, DOI : 10.9780/22307850, http://oldisrj.lbp.world/UploadedData/3138.pdf References : - J. Pérez, R. Pazos , L. Cruz, G. Reyes, R. Basave, and H. Fraire “Improving the Efficiency and Efficacy of the K-means Clustering Algorithm Through a New Convergence Condition”, Gervasi and M. Gavrilova (Eds.): ICCSA 2007, LNCS 4707, Part III, pp. 674–682. Springer-Verlag Berlin Heidelberg 2007.
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- Ganesan, P., and V. Rajini. "Segmentation and edge detection of color images using CIELAB color space and edge detectors." Emerging Trends in Robotics and Communication Technologies (INTERACT), 2010 International Conference on. IEEE, 2010.
- Ganesan, P., and V. Rajini. "A method to segment color images based on modified fuzzy-possibilistic-c-means clustering algorithm." Recent Advances in Space Technology Services and Climate Change (RSTSCC), 2010. IEEE, 2010.
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