To obtain a favorable segmented result of an image, a transition region method, based on the difference of local fuzzy variance between transition region and background, was proposed and used for image segmentation.

Algorithm based on local variance to enhance contrast of fog-degraded image;

Multi-resolution image segmentation method based on local variance;

Fuzzy wavelet thresholding based on local variance for image denoising;

In order to adequately use all kinds of remote sensing image information, some important image fusion techniques, analysis features and disadvantages of these methods are summarized, a novel hierarchical fusion technique for remote sensing image is presented based on local deviation of the direction gradient.

The concept of fuzzy expectation and fuzzy variance is put forward based on expectation and variance.

To improve the performances of transition region extraction algorithms under noises,a novel local fuzzy entropy-based transition region algorithm was proposed by making improvement to the existing local entropy-based transition region algorithm.

By analyzing properties of pixels in noisy images,a novel thresholding method based on local fuzzy entropy and Otsu was presented here.