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Multi-view SAR image segmentation method and device
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An image segmentation and image technology, applied in image analysis, image enhancement, image data processing, etc., can solve problems such as poor anti-noise performance, unsatisfactory segmentation results, and inaccurate SAR image modeling
Inactive Publication Date: 2018-11-09
LIAONING TECHNICAL UNIVERSITY
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The most commonly used mixture model is the GaussianMixture Model (GaussianMixture Model, GMM), which assumes that the gray value of the pixel in the image obeys the Gaussian distribution. However, the weight coefficient in the traditional GMM is represented by a vector and only related to clustering. Single weight, and the SAR image obeys the Gamma distribution, the above problems will cause the traditional GMM to model the SAR image inaccurately
[0004] Aiming at the problems of poor anti-noise performance and unsatisfactory segmentation results of the multi-view SAR image segmentation method mentioned above, no effective solution has been proposed so far.
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Embodiment 1
[0086] figure 1 A schematicflowchart of a multi-view SAR image segmentation method provided by an embodiment of the present invention is shown. The following will be figure 1 The specific process of the shown method is described in detail.
[0087] Step S110, read the multi-view SAR image to be segmented.
[0088] The multi-view SAR image to be segmented is represented by the feature field z:
[0089] z={z i (x i ,y i ):i=1,...,n}
[0090] Among them, i is the pixel index, n is the total number of pixels, z i is the intensity of pixel i, (x i ,y i )∈D is the grid point position of pixel i, and D is the image domain.
[0092] In this embodiment, a double weight w is defined to represent the relationship between a pixel and a category, as follows:
[0093] w i =(w il :l=1,...,k)
[0094] Among them, w il Contains the category weight of pixel i for category l, satisfying k is the number of classes. Among them...
Embodiment 2
[0142] In combination with the foregoing embodiments, this embodiment provides a multi-view SAR image segmentation device, see figure 2 A schematic diagram of the structure of the multi-view SAR image segmentation device shown, the device includes: a reading module 301 , a dual weight initialization module 302 , a weight parameter iterative update module 303 , a category determination module 304 and a display module 305 .
[0143] The details are as follows:
[0144] The reading module 301 is used for reading the multi-view SAR image to be segmented.
[0145] The multi-view SAR image to be segmented is represented by the feature field z:
[0146] z={z i (x i ,y i ):i=1,...,n}
[0147] Among them, i is the pixel index, n is the total number of pixels, z i is the intensity of pixel i, (x i ,y i )∈D is the grid point position of pixel i, and D is the image domain.
[0148] The dual weight initialization module 302 is configured to initialize the dual weight w.
[0149]...
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Abstract
The invention provides a multi-view SAR image segmentation method and device. The method comprises: reading a to-be-segmented multi-view SAR image; initializing a double-weight w; repeating the steps of calculating a Gamma distribution scale parameter beta, calculating a probability p(z|w) of the image, calculating a distribution function p(w) of the double-weight w, calculating a quality function L, updating the double-weight w according to a gradient method, substituting the updated double-weight w into the quality function L, and stopping executing the above steps until |L(t + 1) - L(t)| is less than a preset threshold epsilon, and then determining the category of each pixel in the above image according to the current double-weight w; and outputting a segmentation result according to the category of each pixel. The method has good anti-noise performance in image segmentation, the segmentation result has less mis-classification, and fitting of the segmentation boundaries is accurate.
Description
technical field [0001] The present invention relates to the technical field of image segmentation, in particular to a multi-view SAR image segmentation method and device. Background technique [0002] Synthetic Aperture Radar (SAR) is a high-resolution imaging radar that records the shape of ground objects by receiving the electromagnetic waves scattered by the target and converting them into images. The inherent speckle noise caused by its unique imaging mechanism gives the image segmentation a Great difficulty came. Although multi-look technology can reduce part of the noise, there are still a lot of speckle noise in multi-look SAR images in practical applications. Therefore, the anti-noise and accuracy of multi-look SAR image segmentation methods have always been a hot research issue. [0003] At present, the methods of multi-view SAR image segmentation mainly include: threshold method, boundary method, clustering method and statistical model method. Among them, the mos...
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