Collaborating filtering using unsupervised learning for image reconstruction from missing data

EURASIP Journal on Advances in Signal Processing

Table 1 PSNR values of the reconstructed images using different ratios

Image	Method	15% missing data	25% missing data	35% missing data
Lena	FPC	46.2950	45.8888	45.6461
	ALM	48.2790	48.2248	45.5295
	IALM	48.2673	48.2278	46.0819
	PPG	45.0964	41.9579	40.2865
	PG	45.0966	41.9582	40.2863
	SVT with power method	48.3221	48.2745	48.2295
	Proposed approach	48.9848	48.7817	48.5952
Cameraman	FPC	28.2855	32.3433	31.7894
	ALM	36.8075	33.9694	29.5169
	IALM	36.7101	33.9849	29.8495
	PPG	31.3222	27.9425	24.3797
	PG	31.3199	27.9458	24.3757
	SVT with power method	40.9528	40.5182	40.0158
	Proposed approach	43.3525	42.4823	40.4596
Flinstones	FPC	28.9102	37.4826	37.2896
	ALM	42.9923	37.3583	34.3512
	IALM	42.8769	37.4573	34.6774
	PPG	31.5781	29.5989	24.3693
	PG	31.5936	29.5887	24.3708
	SVT with power method	43.6614	43.5614	43.2075
	Proposed approach	47.8234	47.3814	44.3920
House	FPC	28.6407	27.7999	27.4826
	ALM	37.0989	36.4579	36.3583
	IALM	36.8952	36.5262	36.4573
	PPG	31.5992	29.8729	29.5998
	PG	31.6005	29.8769	29.5701
	SVT with power method	38.1457	38.0827	37.6494
	Proposed approach	39.0707	38.1743	37.8234
Man	FPC	39.2493	38.5864	38.1565
	ALM	41.3640	41.2133	40.4455
	IALM	41.2952	41.2191	40.8616
	PPG	39.4997	39.1895	39.3266
	PG	39.5008	39.1889	39.3264
	SVT with power method	42.9572	42.4158	42.0357
	Proposed approach	44.3212	43.9939	43.6724

For each test setting, six results are provided: FPC, ALM, IAM, PPG, PG, SVT with power method, and our proposed model. The best value of the PSNR is the number written in italics on each row