Remote Sensing Image Reconstruction Based on Improved Adaptive Tensor Nuclear Norm Minimization

Table 1

Quantitative evaluation of disparate methods on the emulated data in disparate conditions.

Noise case	Evaluation index	Noise	ALS	ALM	LRTL	AWTC	TDL	TTSGD
Case 1	MPSNR (dB)	28.35	46.32	39.48	34.59	36.15	35.22	34.68
	MSSIM	0.3485	0.9856	0.9712	0.931	0.9564	0.9416	0.8934
	ERGAS	245.21	22.10	23.26	26.25	30.25	31.26	40.29
Case 2	MPSNR (dB)	22.65	44.26	42.15	39.25	34.21	36.21	32.15
	MSSIM	0.3324	0.9901	0.9851	0.9726	0.8901	0.9015	0.8541
	ERGAS	268.25	25.21	26.29	50.26	101.27	104.58	52.16
Case 3	MPSNR (dB)	15.16	43.25	43.26	37.25	29.54	25.62	30.21
	MSSIM	0.1815	0.9908	0.9874	0.9526	0.9154	0.8564	0.8705
	ERGAS	492.56	25.26	26.25	37.85	108.36	91.25	58.17
Case 4	MPSNR (dB)	17.25	42.65	41.10	39.32	27.24	28.11	33.58
	MSSIM	0.1814	0.9915	0.9899	0.9846	0.8436	0.8245	0.8801
	ERGAS	531.21	23.25	23.98	56.44	123.25	129.00	62.15