High resolution SAR image target detection method based on part model

Abstract

The invention belongs to radar remote sensing or image processing technology, namely, analyzing radar observation information by using image processing technology, and specifically relates to a high resolution SAR image target detection method based on a part model. According to the invention, through performing characteristic compression and screening on each pixel point of original SAR image data, low-level characteristic interest points are extracted, a target part initial unit is generated from interest point local information, calculating initial unit characteristics, generating a target part combination model through an image segmentation method and realizing high resolution SAR image target detection by utilizing description of the target part model. According to the invention, distribution characteristics of a target in the high resolution SAR image are utilized fully and effectively. The target part model obtained through detection is comparatively complete, so that the integral information of a target can be kept well. The method is good in noise robustness, high in algorithm stability, accurate in detection result and can improve the self-adaptive capability of image detection.

Description

technical field [0001] The invention belongs to radar remote sensing or image processing technology, which uses image processing technology to analyze radar observation information, and specifically relates to the application of dynamic component models in synthetic aperture radar (SAR) image target detection. Background technique [0002] Traditional SAR image target detection algorithms are difficult to apply to high-resolution SAR images. With the wide application of high-resolution SAR images, designing accurate target detection algorithms is very important for solving various threats faced by current radars and improving radar signal detection capabilities. Significance. The target in the high-resolution SAR image shows distributed characteristics, and the target is composed of multiple scattering centers in space. With the advancement of high-resolution SAR imaging technology, the algorithm research of target detection in high-resolution SAR images has become a hot sp...

AI Technical Summary

Problems solved by technology

P.F. Felezenszwalb and others directly trained the image to obtain the probability combination criterion of the target component model, and then detected it from top to bottom through the matching method. Therefore, the model extracted by this method comes from the real image and fully utilizes the target information, but its The disadvantage is also very obvious. Since the target model matching requires multiple image space searches, there are a lot of repeated calculations, especially as the amount of data increases, this disadvantage will become more obvious

R. Mottaghi et al. proposed a hybrid method for learning component models, which realized the dynamic characteristics of component models and improved the flexibility of algorithm design, but its criteria were optimized for optical images, not suitable for processing SAR images

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