Research Article

Combined First- and Second-Order Variational Model for Image Compressive Sensing

Table 1

PSNRs of the reconstructed images.

Sampling ratio (%)20253350
Noise level (dB)3040304030403040

Lena (256 × 256)
TVAL326.9927.1428.1227.6529.0329.1931.5132.34
RecPF29.9330.9230.7632.0632.0134.0634.0337.94
Hybrid TVL130.1231.1330.9732.2632.2434.4334.2638.41
Second-order TV30.5731.5231.8933.8732.8336.0934.7440.08
Our method31.0532.7432.9334.1232.9936.4134.4340.24

Pepper (256 × 256)
TVAL330.0830.4130.7532.2332.7833.9335.0838.08
RecPF30.9231.9531.7233.7933.0135.6834.9139.25
Hybrid TVL131.1032.2931.9334.1033.2436.0535.0639.65
Second-order TV31.7233.7631.7235.7933.6737.6735.0741.07
Our method32.2534.2432.6636.1833.7737.9634.8241.21

Barbara (256 × 256)
TVAL327.2527.5727.7828.2729.1429.4531.4232.45
RecPF28.7029.2929.4530.2830.6731.8033.0735.62
Hybrid TVL128.8629.5029.6330.5530.9332.2033.3636.20
Second-order TV29.2530.2130.0231.5431.4133.4433.8637.98
Our method29.6230.6930.4631.8631.6933.7633.8938.13

Brain (256 × 256)
TVAL332.6333.2233.7634.4935.2336.3237.5240.18
RecPF31.4932.1132.5133.5033.8935.2736.3139.12
Hybrid TVL131.6932.3832.7533.8334.2335.7536.6339.71
Second-order TV32.6533.6433.6635.1335.2037.2937.5241.11
Our method33.1934.7234.0235.6335.4637.7037.3541.55