Table 1. Comparison of proposed method with average, weiner, median filters using different evalualtion measures.

	Original image vs noise introduced image			Orignal image vs output images of average, weiner and median filters				Original image vs output image of proposed method
Image (resolution)	PSNR	F -measure	NRM	Filter	PSNR	F- measure	NRM	PSNR	F-measure	NRM
Image no.1 (1822×1590)	19.14 dB	94.5251%	4.84555	Average	18.36 dB	81.473%	7.15771	22.77 dB	82.3644%	1.09061
				Weiner	14.89 dB	32.154 %	4.31239
				Median	18.26 dB	79.5219%	6.40972
Image no.2 (802×1537)	18.64 dB	92.3455%	6.03096	Average	12.18 dB	73.7318%	20.787	22.46 dB	96.6344%	1.40903
				Weiner	11.46 dB	29.1663%	6.94014
				Median	18.62 dB	92.0617%	5.01784
Image no.3 (1633×872)	19.43 dB	92.4561%	6.21288	Average	19.12 dB	92.049%	7.0705	22.79 dB	96.2263%	0.792766
				Weiner	14.49 dB	67.4895%	3.00505
				Median	20.27 dB	93.5766%	4.14711
Image no.4 (1784×2703)	23.02 dB	95.9232%	2.49492	Average	19.53 dB	91.3193%	6.77008	24.01 dB	96. 6342%	0.37392
				Weiner	14.13 dB	53.6225%	2.56231
				Median	20.30 dB	92.2412%	3.75177
Image no.5 (1497×2338)	22.57 dB	96.7135%	2.48476	Average	19.13 dB	92.7348%	6.27126	24.64 dB	97.7949%	0.483374
				Weiner	12.72 dB	49.4689%	3.42444
				Median	21.48 dB	95.5001%	2.39183