Research Article

A New Boosting Algorithm for Shrinkage Curve Learning

Table 2

Comparison of several denoising results under different noise levels. Test images are from MeasTex texture database.

Image
OursImpvOursImpvOursImpv

Fabric35.9335.9437.191.2631.6631.6632.650.9929.5029.5030.200.71
Food35.3535.3736.060.7130.5330.5431.160.6328.0828.0828.530.45
Leaves37.3737.3641.664.2834.0634.0437.893.8332.5332.5135.743.20
Water36.2436.2637.631.3931.7831.8033.121.3429.3329.3530.681.36
Wood37.0737.0639.182.1133.4533.4435.441.9931.6031.5833.221.62
Image
OursImpvOursImpvOursImpv
Fabric28.0428.0228.550.5126.9226.8927.310.3923.6723.7123.860.19
Food26.4826.4726.800.3325.3025.2825.560.2522.0122.0222.310.30
Leaves31.4431.4334.142.7030.4430.4632.892.4526.0026.3828.952.95
Water27.6027.5729.021.4226.2426.1127.751.5122.1522.0923.961.80
Wood30.2630.2331.621.3629.1629.1130.441.2825.3325.4026.721.39