Measurement Matrix Optimization via Mutual Coherence Minimization for Compressively Sensed Signals Reconstruction

Figure 6

The reconstructed images Building by measurement matrices of (a) sparse random (PSNR: 24.0906 dB, SSIM: 0.44499), (b) Gaussian (PSNR: 24.5570 dB, SSIM: 0.45856), (c) Bernoulli (PSNR: 24.0547 dB, SSIM: 0.44028), (d) part Hadamard (PSNR: 24.8548 dB, SSIM: 0.47995), (e) No Regularization (PSNR: 24.1901 dB, SSIM: 0.44146), (f) Elad’s method (PSNR: 24.9355 dB, SSIM: 0.47619), (g) Wang’s method (PSNR: 25.9409 dB, SSIM: 0.56286), and (h) our proposed method (PSNR: 27.6707 dB, SSIM: 0.61185) at  = 128 and  = 512.

(a)

(b)

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(e)

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(h)