Scale self-adaptive image segmentation method
A scale-adaptive, image segmentation technology, applied in image enhancement, image data processing, instruments, etc., can solve the problem of lack of a quantitative standard
Inactive Publication Date: 2007-09-19
SECOND INST OF OCEANOGRAPHY MNR
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The multi-scale analysis method uses the multi-scale segmentation results for image classification, but the selection of segmentation scales at home and abroad lacks a quantitative standard
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[0040] The definition of significance in the present invention includes the pixel value distance between map spots and the standard deviation of map spot pixel values. From the perspective of classification based on pixels, it can be regarded as distance between groups and discreteness within groups, which is similar to a A commonly used supervised classification method-Fischer linear discrimination, that is, the distance between groups (mean difference) is the largest, and the dispersion within the group (sum of squared deviations) is the smallest. The difference is that Fisher linear discrimination has no space for the two categories of data. However, here we restrict the two types of pixel sets in space, that is, the spots are adjacent, and the pixels in the spots are spatially connected by four domains. The minimum distance of a patch reflects the distance between the pixel value of the patch and its adjacent patches, the standard deviation of the patch reflects the uniform...
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The invention discloses a size self-adaptive image segmentation method comprising following steps: 1) images and one or more image layers of converted results of the images determining an image gather to be segmented; 2) setting a segmentation method and a size increasing manner, and segmenting the images by a continuous variated size coefficient; 3) segmented results in different sizes forming a tree-structure image object expression based on combined relationships between image speckles; (4) defining markedness of image speckles; (5) image speckles segmented with continuous variated sizes composing an image speckle development curve; (6) forming a markedness curve and a segmentation beginning curve of the image speckles in a segmentation development process; (7) calculating extremums in the markedness curve to form a size reverse order; 8) forming an extremum size image according to the extremums in the size reverse order; 9) determining segmentation image speckles based on predominance sizes in the extremum size image. The invention defines an optimum segmentation size of the iamge object according to self-properties of the image speckles so that objects with different sizes have condign segmentation sizes, respectively.
Description
technical field [0001] The invention relates to the technical field of image segmentation and image understanding, in particular to a scale-adaptive image segmentation method. Background technique [0002] Image segmentation is an important algorithm for image processing, and there are already many algorithms. Image segmentation method is an important means to improve the classification accuracy and extract ground object information in remote sensing image processing. The image segmentation method realizes the formation of spot objects in remote sensing images. [0003] There are two main image segmentation techniques [1, 2], one is based on edge detection, and the closed curve formed by edge tracking forms small spots; the other is based on Based on region growth, similar pixels are combined into spots according to a specific discriminant function, such as multi-scale analysis methods in remote sensing image processing. The principle of the region-based segmentation metho...
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Inventor 陈建裕
Owner SECOND INST OF OCEANOGRAPHY MNR