EURASIP Journal on Advances in Signal Processing

Table 3 SSIM for additive Gaussian noise

From: A collaborative adaptive Wiener filter for image restoration using a spatial-domain multi-patch correlation model

Image	Method	SSIM
		σ _η *=10*	σ _η *=20*	σ _η *=30*	σ _η *=40*
Aerial	Corrupted	0.9719	0.9046	0.8224	0.7388
491×434	NLM	0.9753	0.9058	0.8412	0.7872
	GLIDE-NLM	0.9747	0.9058	0.8427	0.7916
	PLOW	0.9734	0.9252	0.8760	0.8282
	BM3D	0.9783	0.9340	0.8835	0.8287
	AWF	0.9762	0.9304	0.8804	0.8322
	CAWF	0.9787	0.9351	0.8859	0.8365
Bridge	Corrupted	0.9542	0.8512	0.7365	0.6305
512²	NLM	0.9611	0.8651	0.7925	0.7379
	GLIDE-NLM	0.9621	0.8757	0.8010	0.7363
	PLOW	0.9587	0.9051	0.8485	0.7943
	BM3D	0.9692	0.9126	0.8539	0.7963
	AWF	0.9652	0.9061	0.8477	0.7927
	CAWF	0.9676	0.9109	0.8523	0.7985
River	Corrupted	0.9512	0.8429	0.7252	0.6196
(Kodak 11)	NLM	0.9525	0.8343	0.7588	0.7042
768×512	GLIDE-NLM	0.9548	0.8461	0.7617	0.7007
	PLOW	0.9505	0.8732	0.7921	0.7299
	BM3D	0.9597	0.8792	0.8066	0.7437
	AWF	0.9574	0.8823	0.8142	0.7512
	CAWF	0.9609	0.8873	0.8207	0.7634
Bones	Corrupted	0.9259	0.7735	0.6224	0.4979
512×768	NLM	0.9329	0.7946	0.7269	0.6821
	GLIDE-NLM	0.9379	0.8163	0.7351	0.6725
	PLOW	0.9240	0.8295	0.7587	0.7047
	BM3D	0.9417	0.8404	0.7641	0.7091
	AWF	0.9389	0.8459	0.7669	0.6970
	CAWF	0.9439	0.8551	0.7839	0.7277
Building	Corrupted	0.9153	0.7660	0.6349	0.5318
768×512	NLM	0.9395	0.8370	0.7808	0.7386
	GLIDE-NLM	0.9426	0.8416	0.7835	0.7385
	PLOW	0.9379	0.8577	0.7823	0.7262
	BM3D	0.9482	0.8748	0.8141	0.7637
	AWF	0.9398	0.8583	0.7797	0.7072
	CAWF	0.9502	0.8788	0.8190	0.7665
Gazebo	Corrupted	0.9130	0.7678	0.6428	0.5435
768×512	NLM	0.9561	0.8653	0.8090	0.7649
	GLIDE-NLM	0.9578	0.8712	0.8117	0.7686
	PLOW	0.9525	0.8698	0.8046	0.7559
	BM3D	0.9620	0.8963	0.8397	0.7940
	AWF	0.9452	0.8740	0.7950	0.7230
	CAWF	0.9611	0.8988	0.8387	0.7837

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