基于噪声灰度差估计三维显微图像超分辨率复原

提出了基于噪声灰度差估计的图像复原方法.在带斑点图像复原的过程中,用不同方向的均匀算子与图像进行卷积,再与原图像相减,取灰度差最小值构成噪声灰度差估计图.由此图获得斑点的强度和位置,进而对斑点进行邻域平均处理以保证复原效果.测试结果表明,噪声灰度差估计能够准确反映图像斑点的强度和位置定位,并且运算量小.该方法应用于三维显微图像复原的结果表明,斑点亮度得到有效控制,小斑点被去除,获得了良好的超分辨率复原效果.

Super-Resolution Restoration of Three Dimensional Microscopic Image Based on Estimation of Noise Gray Scale Difference

An image restoration method based on noise gray scale difference estimation is proposed. In order to ensure the quality of restored punctate image, the image is convoluted respectively by various directional uniform arithmetic operators, and the results from convolution are subtracted respectively from the original images. The estimation image of noise gray scale difference is constructed by extracting the pixels with minima of gray scale differences. Then, the intensity and the position of the spot in the image can be got, and the spots are smoothed by neighboring pixels. Test results show that noise gray scale difference estimation can express exactly intensity and position of the spots in the punctate image with small operation amount needed. The proposed method has been used experimentally to restore three dimension biological microscopic image, and its results show that the lighteness of spots is controlled efficiently and small spots are wiped off in restored image. The image restoration with super-resolution is achieved with good effect.