A Fast SAR Image Target Detection Method Based on Optimal Entropy Dual Threshold Segmentation
A target detection and double-threshold technology, applied in the field of image recognition, can solve the problems of non-real-time performance, low algorithm detection efficiency, and influence on detection results, etc., and achieve the effect of being beneficial to detection extraction, engineering application, and high detection efficiency
Active Publication Date: 2020-12-01
XIAN MICROELECTRONICS TECH INST
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[0004] The CFAR method based on the background statistical model distribution and its improved algorithm are a kind of adaptive detection algorithm. Under the premise of ensuring the constant false alarm rate, this kind of method adaptively selects the threshold according to the statistical information of the SAR image, and selects the threshold from the complex Extracting targets in sea clutter environment, this kind of method has the following deficiencies and defects: the accuracy of modeling the sea clutter statistical model will directly affect the detection results; complex mathematical modeling is not conducive to engineering realization; this kind of method is mainly applicable For medium and low resolution SAR images, the detection effect on high resolution SAR images is not ideal; the algorithm needs to set parameters such as target window and protection window according to prior information, and the idea of local sliding window makes the detection efficiency of the algorithm very low. Low, not real-time in practical applications
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[0028] The present invention is described in further detail below in conjunction with accompanying drawing:
[0029] The present invention provides a fast SAR image target detection method based on optimal entropy double-threshold segmentation, such as figure 1 shown, including the following steps:
[0030] Step 1, input the original SAR image; the original SAR image contains the ship target, and the size is a 4000×4000 sea area image;
[0031] Step 2, perform contrast enhancement preprocessing on the original SAR image; such as figure 2 As shown, the unprocessed original SAR image data format is 16 bits, and the grayscale range is 0 to 65536. However, observing the grayscale histogram distribution, the grayscale value basically has no pixel distribution in a large range, so the image is darker. , in order to facilitate observation and analysis, the image is first stretched in gray scale. The specific process is: truncate the maximum and minimum 0.15% of the gray histogram...
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The invention discloses a fast SAR image target detection method for optimal entropy double-threshold segmentation, which is characterized in that it comprises the following steps: inputting an original SAR image; performing contrast enhancement preprocessing on the original SAR image, and then suppressing coherent speckle noise of the image , to obtain a gray-scale enhanced image; use the center-periphery algorithm to extract and obtain the image features of the center-neighborhood difference of the gray-scale enhanced image; weighted and summed the gray-scale enhanced image and feature map to obtain a new image; The image is segmented to obtain the final binary detection result. The method realizes rapid separation and extraction of targets in high-resolution SAR images while ensuring a high detection rate. The method is simple and easy to implement.
Description
technical field [0001] The invention belongs to the technical field of image recognition, and relates to a fast SAR image target detection method based on optimal entropy double-threshold segmentation. Background technique [0002] The SAR system has all-weather, all-time imaging capabilities and certain penetration, and has been widely used in military and civilian fields. In recent years, the use of SAR images to detect and monitor ship targets has become an important aspect of SAR image marine application research. [0003] The essence of ship target detection algorithm in SAR images is to complete the target detection according to the characteristic difference between the target and the clutter scattering characteristics. The detection algorithm based on gray features can quickly and accurately detect ship targets in a wide sea area. Such detectors are often the core of ship target detection algorithms and are widely used in existing ship target detection systems. Such...
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IPC IPC(8): G06T7/136G06K9/00
CPCG06T7/136G06T2207/10044G06V20/13G06V2201/07
Inventor 王莉马钟
Owner XIAN MICROELECTRONICS TECH INST