According to the B-spline convolution mask, first, the contrast sensitiveness （CS） is computed and then is viewed as a noise sensitiveness coeficient （NSC） to adaptively determine a noise-recognized threshold valu...According to the B-spline convolution mask, first, the contrast sensitiveness （CS） is computed and then is viewed as a noise sensitiveness coeficient （NSC） to adaptively determine a noise-recognized threshold value. Based on the noise density function （NDF） in a 3×3 window, the filtering window size is adaptively adjusted, and then a median filter is used to eliminate the noise-marked pixels. The experiment results show that the proposed algorithm can preserve image detail information well and effectively remove the noises, particularly the impulse noises that is also called salt-and-pepper noises superimposed on the computed tomography （CT） and magnetic resonance imaging （MRI） medical images.展开更多
基金supported by Foundation of 11th Five-year Plan for Key Construction Academic Subject (Optics) of Hunan Province,PRC, Outstanding Young Scientific Research Fund of Hunan Provincial Education Department, PRC (No. 09B071)Scientific Research Fund of Hunan Provincial Education Department, PRC(No. 06C581)
文摘According to the B-spline convolution mask, first, the contrast sensitiveness （CS） is computed and then is viewed as a noise sensitiveness coeficient （NSC） to adaptively determine a noise-recognized threshold value. Based on the noise density function （NDF） in a 3×3 window, the filtering window size is adaptively adjusted, and then a median filter is used to eliminate the noise-marked pixels. The experiment results show that the proposed algorithm can preserve image detail information well and effectively remove the noises, particularly the impulse noises that is also called salt-and-pepper noises superimposed on the computed tomography （CT） and magnetic resonance imaging （MRI） medical images.
