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Method for detecting SAR image changes of cluster-based higher order cumulant cross entropy

An image change detection and cross-entropy technology, applied in the field of image processing, can solve the problems of inaccuracy, extraction, loss of detection results of small target change details, etc., and achieve the effect of improving detection accuracy and detection effect.

Active Publication Date: 2010-06-16
XIDIAN UNIV
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Problems solved by technology

[0004] Although various change detection methods have been widely used in many fields, overall, the detection effect of change detection on small targets still has the problem of serious loss of change details and inaccurate detection results when the change range is small. and the problem that the target cannot be clearly extracted from the noise in the binary image

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  • Method for detecting SAR image changes of cluster-based higher order cumulant cross entropy
  • Method for detecting SAR image changes of cluster-based higher order cumulant cross entropy
  • Method for detecting SAR image changes of cluster-based higher order cumulant cross entropy

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Embodiment Construction

[0023] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0024] Step 1. Select two SAR images with different phases.

[0025] The experimental images are selected from two SAR images of water targets in different phases, such as figure 2 shown, where figure 2 (a) is the first phase, figure 2 (b) is the second time phase, and the change information is the change of the target in the water area. The SAR images of these two different time phases contain the target change information, and the size of the two SAR images is 318×318, record the image side length is R, R=318.

[0026] Step 2. Extract pixels of the same category as the window center point in the window, the specific steps are as follows:

[0027] 1a) Taking the coordinates (i, j) as the center, take a window W whose side length is R / 6 1 and W 2 , use the K-means clustering method to cluster the pixels in the window into M categories, M∈[6,10];

[0028] 1b) Calcu...

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Abstract

The invention discloses a method for detecting SAR image changes of cluster-based higher order cumulant cross entropy, which mainly overcomes the defect that in the existing model method detection, the detection result is inaccurate under the condition with a small variation range. The method comprises the following implementation processes: (1) extracting pixel points of a window by using a K mean clustering method; (2) eliminating redundant pixel points by using Euclidean distance; (3) using the extracted pixel points of the window as samples to perform higher order cumulant-based cross entropy algorithm computation to obtain a change difference image; (4) processing the difference image by a maximum inter-class variance threshold method to obtain a binary image; and (5) considering a neighborhood relation to the binary image to perform neighborhood-based de-noising operation so as to obtain a final change detection result. The method has the advantage of detecting small target changes, and can be used for detecting objects of multi-date SAR image changes.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to an image target change detection method, which is suitable for the change detection that contains target change information in two different phase SAR images and is seriously polluted by noise. Background technique [0002] The purpose of change detection is to obtain the interesting information about the change of ground features through the difference between images in different periods in the same area. The key technologies in earth observation applications have urgent needs and broad application prospects. Synthetic aperture radar (SAR) has the characteristics of all-weather and all-time, and it is a good source of change detection information. The research on SAR image change detection technology has a very broad application prospect. [0003] Change detection is a key and hot issue in the field of remote sensing. Many scholars have classified and analyzed the existi...

Claims

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Application Information

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IPC IPC(8): G01S7/41G01S13/90G06T7/00
Inventor 焦李成张小华张静侯彪刘芳王爽马文萍张向荣
Owner XIDIAN UNIV
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