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

Table 2

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)	25.67	50.29	48.26	40.26	29.26	44.26	34.39
	MSSIM	0.2935	0.9526	0.9478	0.8963	0.9435	0.9528	0.8816
	ERGAS	195.25	19.26	20.35	24.59	27.36	28.26	44.28
Case 2	MPSNR (dB)	17.56	39.96	39.56	32.56	34.75	33.24	30.19
	MSSIM	0.2486	0.9825	0.9545	0.9878	0.8548	0.9245	0.8274
	ERGAS	27.22	19.48	19.99	48.25	110.24	108.55	79.54
Case 3	MPSNR (dB)	12.01	48.65	37.55	34.26	29.08	26.55	27.25
	MSSIM	0.1938	0.9810	0.9744	0.9556	0.9121	0.8377	0.8648
	ERGAS	535.53	18.11	18.22	31.24	100.14	98.24	40.22
Case 4	MPSNR (dB)	11.99	39.22	38.65	37.14	28.26	29.33	31.02
	MSSIM	0.1639	0.9715	0.9156	0.9815	0.8021	0.7748	0.8125
	ERGAS	519.26	20.55	22.10	57.15	118.26	131.05	55.28