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Presentation of the Adaptive Filters A usual problem which arises in many image processing applications is the corruption of images by different kinds of noise, which leads to the degradation of their perceived quality. To deal with this problem, researchers in the field of image processing and analysis, have developed, over the years, various filtering algorithms for noise removal. Three adaptive nonlinear order statistics filters for noise removal are:
Performance Results For the comparison of the performance of the proposed filters, a reference image called has been corrupted by the contaminated gaussian noise model: The performance results in respect with SNR, PSNR, MAE and MSE, measured on the processed versions of a noisy image by the adaptive L, by the adaptive Ll, by the symmetrical SAM and by the morphological SAM filters, are concentrated in the following table: The observation of both performance results and processed images leads to the following conclusions:
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S. Tsekeridou, C. Kotropoulos and I. Pitas, "Adaptive Order Statistic Filters for the Removal of Noise from Corrupted Images", SPIE Optical Engineering, vol. 37, no. 10, pp. 27982816, October, 1998. C. Kotropoulos and I. Pitas, "Adaptive LMS Lfilters for Noise Suppression in Images", IEEE Transactions on Image Processing, vol. 5, no. 12, pp. 15961609, December, 1996. S. Tsekeridou, C. Kotropoulos and I. Pitas, "Morphological Signal Adaptive Median Filter for Noise Removal", in Proc. of 1996 Int. Conf. on Electronics, Circuits and Systems (ICECS'96), vol. 1, pp. 191194, Rodos, Greece, 1316 October, 1996.
 

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