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Algorithm for detection of changing regions in sar images based on neighborhood ratio and self-paced learning

A technology of region detection and image change, applied in the field of image processing, can solve the problems of increasing the false detection rate of late change detection, loss of texture information, containing artificial parameters, etc., and achieve the effect of improving self-learning ability, accuracy and precision.

Active Publication Date: 2019-11-01
XIDIAN UNIV
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Problems solved by technology

The disadvantage of this method is that the algorithm contains artificial parameters, which requires multiple tests to obtain the optimal parameter value, and it is not easy to automatically select according to the nature of the image itself.
The disadvantage of this method is that the error control in the dictionary learning is in the actual operation, which will easily cause the loss of part of the texture information of the image, and increase the false detection rate of the later change detection.

Method used

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  • Algorithm for detection of changing regions in sar images based on neighborhood ratio and self-paced learning
  • Algorithm for detection of changing regions in sar images based on neighborhood ratio and self-paced learning
  • Algorithm for detection of changing regions in sar images based on neighborhood ratio and self-paced learning

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Embodiment Construction

[0038] The present invention will be further described below in conjunction with the accompanying drawings.

[0039] refer to figure 1 , the concrete realization steps of the present invention are as follows:

[0040] Step 1, read in the synthetic aperture radar SAR image.

[0041] Read in two registered and corrected Synthetic Aperture Radar SAR images in different phases of the same area I 1 and I 2 .

[0042] Step 2, normalization.

[0043] Using the following equation, for the synthetic aperture radar SAR image I 1 and I2 The normalization process is carried out respectively, and the normalized synthetic aperture radar SAR image I is obtained. 1 ' and I 2 ':

[0044]

[0045]

[0046] Among them, I 1 ' denotes the synthetic aperture radar SAR image I 1 Normalized synthetic aperture radar SAR image, min represents the operation of taking the minimum value, max represents the operation of taking the maximum value, I 2 ' denotes the synthetic aperture radar S...

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Abstract

The invention discloses a synthetic aperture radar (SAR) image change region detection method based on neighborhood ratio and self-stepping learning, and mainly solves the problem that the prior art is sensitive to speckle noise of an SAR image, and the problem that part of texture information of the SAR image is lost easily. The method comprises the specific steps of (1) reading an SAR image; (2)normalizing; (3) calculating a neighborhood ratio difference value; (4) constructing a difference value matrix; (5) selecting a training sample set; (6) training a deep belief network; (7) constructing a probability matrix; (8) updating a probability matrix; (9) obtaining a change detection image. According to the method, the local information of an original image and the self-learning capabilityof a deep belief network are effectively utilized, and speckle noise is reduced, the partial image information is kept, and the precision of change detection is improved.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a synthetic aperture radar SAR (Synthetic Aperture Radar, SAR) image change area detection method based on neighborhood ratio and self-learning in the remote sensing image change detection technical field. The invention can be used to compare the neighborhood pixel information of two synthetic aperture radar SAR images in the same area at different time periods to obtain a change difference map, and use the self-step learning algorithm to segment the difference map to obtain a change detection map. Background technique [0002] As an active microwave sensor, synthetic aperture radar has the characteristics of high resolution, all-weather, all-day operation and strong penetrating power, which makes synthetic aperture radar SAR have the incomparable advantages of optical remote sensing images. The synthetic aperture radar SAR image change detection technology is to s...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T7/41
Inventor 刘若辰焦李成王锐楠李建霞冯婕李阳阳张向荣
Owner XIDIAN UNIV
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