SAR image water area automatic detection method based on recursive OTSU algorithm

Abstract

The invention discloses an SAR image water area automatic detection method based on a recursive OTSU algorithm. The method is characterized by obtaining SAR image power data, and carrying out coherent speckle filtering on the SAR image power data to obtain SAR image power data obtained after coherent speckle filtering; carrying out normalization on the SAR image power data obtained after coherent speckle filtering to obtain normalized SAR image data; carrying out graying processing on the normalized SAR image data to obtain an SAR gray image; carrying out threshold estimation on the SAR gray image to determine an optimum threshold value of the SAR gray image; constructing a matrix same with the SAR image power data and recording the matrix as a mark matrix; according to the optimum threshold value of the SAR gray image, obtaining a binary mark matrix corresponding to the SAR image power data; and finally, carrying out morphological processing on the binary mark matrix corresponding to the SAR image power data to obtain a water area detection mark graph of the SAR image power data.

Description

technical field [0001] The invention relates to the technical field of synthetic aperture radar detection, in particular to a method for automatic detection of SAR image waters based on a recursive OTSU algorithm, that is, an automatic detection method for SAR image waters based on a recursive maximum between-class variance (OTSU) algorithm, which is suitable for adaptive extraction The water part in the SAR image, and then complete the real-time monitoring of the dynamic changes of the water body. Background technique [0002] Synthetic Aperture Radar (SAR) has been widely used due to its all-weather and all-weather monitoring capabilities. So far, countries around the world have successfully launched many advanced space-borne SRA satellites, such as ALOS-2, Radarsat-2, COSMO-SkyMed, TerraSAR-X, Sentinel-1A / B and Gaofen-3, etc. They are synthetic aperture Various applications of radar provide effective data support. [0003] SAR images contain water areas, vegetation area...

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Problems solved by technology

[0004] In the article "Automatic Extraction of Water Bodies fromTerraSAR-X Data", T.Hahmann et al. used a threshold-based detection method for water extraction, that is, the pixels in the SAR image whose backscatter coefficient value is less than or equal to a given threshold are marked as water ; The threshold-based detection method has a faster detection speed, so it is very suitable for batch processing of large-scale data; however, the threshold-based detection method still has the following problems: in general, due to specular scattering, the back of the water area However, when the surface of the water body has fluctuations due to the influence of the environment (such as wind speed, precipitation, etc.), the backscatter coefficient of the water area will also increase. When the data is used for water area detection, the water area detection threshold of different SAR images needs to be determined separately; when different SAR image data are processed in batches, the determination of the water area detection threshold will consume a lot of time, which seriously reduces the efficiency of batch processing multiple SAR image data

However, the acquisition of the high and low thresholds in this paper is based on the analysis of about 1,700 SAR images around the world and obtained through statistical methods, which lacks objectivity

[0006] At present, for the batch and efficient processing requirements in SAR image water detection, the detection method based on threshold is a good choice, but it cannot realize the efficient and automatic processing of SAR image water detection

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