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EURASIP Journal on Advances in Signal Processing
Fig. 9 | EURASIP Journal on Advances in Signal Processing

Fig. 9

From: Hyperspectral image denoising and destriping based on sparse representation, graph Laplacian regularization and stripe low-rank property

Fig. 9

Change in the MPSNR values of Proposed method for the Pavia City Center image (top) and the Washington DC Mall image (bottom) by varying parameters \(\lambda\), \(\mu\) and \(\beta\). The data were corrupted by the noise simulated in Case 1 and Case 2 with \(\sigma\) = 0.05 and o = 0.01: a, f r = 0.3, v = 0.075; b, g r = 0.5, v = 0.075; c, h r = 0.7, v = 0.075; d, i r = 0.3, v = 0.05; e, j r = 0.3, v = 0.1;

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