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

Table 1

PSNRs/SSIMs of reconstructed images by different measurement matrices at  = 128.

Images	Sparse random	Gaussian	Bernoulli	Part Hadamard	NoReg	Elad’s	Wang’s	Optimized matrix
Peppers	21.2336/0.33377	21.2234/0.3352	20.9420/0.32786	21.4817/0.34782	21.4106/0.33903	21.4965/0.34668	22.3604/0.4139	24.2672/0.48002
Boats	20.1211/0.32113	20.0598/0.31796	20.1037/0.32355	20.4870/0.34079	21.1489/0.32162	20.3158/0.33196	21.1873/0.3976	23.3487/0.48302
Building	24.0236/0.43797	24.4098/0.44937	24.0987/0.44321	24.7301/0.47496	24.2669/0.44778	24.8264/0.47467	26.1096/0.57190	27.2533/0.58487
Cameraman	21.8334/0.43157	21.5152/0.41978	21.6693/0.41437	22.0669/0.46524	21.6392/0.42525	22.1898/0.45114	22.7035/0.52447	25.8632/0.62734
Barbara	20.1602/0.42315	20.4094/0.43275	20.0468/0.41262	20.5244/0.44034	20.3292/0.43005	20.4563/0.4436	21.8251/0.5315	23.6868/0.6042
Mandrill	16.4434/0.20460	16.4298/0.20306	16.4234/0.20594	16.6225/0.21432	16.6581/0.21474	16.4741/0.20784	16.9468/0.2518	18.1533/0.30182
Goldhill	20.2144/0.29227	20.1329/0.28863	20.1679/0.29005	20.5636/0.31045	20.3922/0.30052	20.4659/0.30194	21.2499/0.37623	23.4258/0.46419
Fingerprint	15.6476/0.25184	15.5595/0.24256	15.5394/0.24149	15.7223/0.25411	15.6447/0.24709	15.6734/0.25524	17.0946/0.38497	17.8569/0.43580