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

Figure 7

The reconstructed images Cameraman by measurement matrices of (a) sparse random (PSNR: 29.9159 dB, SSIM: 0.78685), (b) Gaussian (PSNR: 29.4204 dB, SSIM: 0.77486), (c) Bernoulli (PSNR: 29.3394 dB, SSIM: 0.77426), (d) part Hadamard (PSNR: 31.0353 dB, SSIM: 0.82327), (e) No Regularization (PSNR: 29.8907 dB, SSIM: 0.78744), (f) Elad’s method (PSNR: 31.1338 dB, SSIM: 0.8232), (g) Wang’s method (PSNR: 30.6554 dB, SSIM: 0.82174), and (h) our proposed method (PSNR: 32.0550 dB, SSIM: 0.83511) at  = 256 and  = 512.

(a)

(b)

(c)

(d)

(e)

(f)

(g)

(h)