Synthetic aperture radar image self-adaptive spot noise suppressing method

Abstract

The utility model discloses a silencing method of synthetic aperture radar image self adaptive speckle, providing a standard utilizing a global statistic heterogeneity entropy He to judge regional homogeneous or heterogeneous. Because the heterogeneity entropy He can utilize the global probability and statistics distribution of the image, the changes of edge detail and texture information can be measured accurately. And then the local homogeneous or heterogeneous of the image is judged more accurately and self adaptively utilizes different noise reduction measures. The method can inhibit the speckle noises of synthetic aperture radar image without sacrificing the spatial resolution, and reserve the role of the fringe goals texture edge details.

Description

technical field [0001] The invention belongs to the field of image processing, and relates to a speckle noise suppression method, in particular to an adaptive speckle noise suppression method for synthetic aperture radar images Background technique [0002] Synthetic Aperture Radar (SAR) is not limited by factors such as weather, geography and time. It can perform high-resolution imaging on the ground and has a certain penetrating power. Therefore, it is widely used in military reconnaissance, resource detection, fire, ocean observation, environmental monitoring, etc. [0003] Since SAR works based on the coherent imaging mechanism, there is serious speckle noise in the SAR image, which has a great impact on the interpretation and information extraction of radar images. Early SAR image speckle noise suppression was achieved through multi-view processing. , the main disadvantage of this method is that the spatial resolution of the image is sacrificed, and it is not suitable f...

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Problems solved by technology

[0003] Since SAR works based on the coherent imaging mechanism, there is serious speckle noise in the SAR image, which has a great impact on the interpretation and information extraction of radar images. Early SAR image speckle noise suppression was achieved through multi-view processing. , the main disadvantage of this method is that the spatial resolution of the image is sacrificed, and it is not suitable for the current high-resolution SAR system

[0004] At present, the spatial filtering method is usually used to suppress speckle noise. The spatial filtering method generally uses a sliding window to weight the pixels in the window to obtain the pixel value of the center point of the window. Traditional methods, such as Lee filtering, Kuan Filtering, Frost filtering and Gamma MAP filtering, but the images obtained by the above methods have problems such as blurred edges and texture details. Recent methods, such as improved Lee filtering, use local statistics, that is, the ratio C of the mean and standard deviation under the sliding window v As a weight factor, different filter values ​​are output in the uniform area and the edge area with a relatively sudden change to suppress the speckle noise. This improved Lee algorithm can maintain the abrupt edge to some extent, but the speckle noise in the general SAR image is not only Contains multiplicative noise, also contains additive noise, and C v Only suitable for multiplicative noise models, very sensitive to additive noise, and only local statistics, so edge details and texture information are still not well preserved

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