Abstract
AbstractThe traditional target recognition method for the remote sensing image is difficult to accurately identify the specified targets from the massive remote sensing image data. Based on the theory of multitemporal recognition, an automatic target recognition method for the remote sensing image is proposed in this article. The proposed recognition method includes four modules: automatic segmentation of multitemporal remote sensing image, automatic target extraction of multitemporal remote sensing image, automatic processing of multitemporal remote sensing image, and automatic recognition of multitemporal remote sensing image. The automatic segmentation of the image target is introduced. The effectiveness of the segmentation technology is verified through the kernel function bandwidth algorithm. Linear feature extraction is used to extract the segmented image. The image extraction processing is described, which includes image profile analysis, image preprocessing, image feature analysis, the region of interest localization, image enhancement processing, recognition processing, and result output. According to the theory of pattern recognition, three different feature recognition images are given, which are partial separable recognition, weakly separable recognition, and fully separable recognition, and then, a new image recognition method is designed. To verify the practical application effect of the recognition method, the proposed method is compared with the traditional recognition method. Experimental results show that the proposed method can accurately identify the specified objects from the massive remote sensing image data and has a high potential for development. This article has an important guiding significance for image recognition.
Highlights
With the development of the remote sensing technology, the spectrum and the spatial and temporal resolution of remote sensing imaging have been improved continuously, which makes the image data of remote sensing sensors to be collected and transmitted to the ground rapidly
With the characteristics of TMS320VC5402 (Temperature Measurement Society), we focus on the preprocessing algorithm and digital signal processing (DSP) implementation
Because there is no systematic use of knowledge, and it has a difference in the visual mechanism of target recognition, the traditional method has the problem of the complex algorithm and the low degree of knowledge sharing and reuse [21,22,23,24,25]
Summary
With the development of the remote sensing technology, the spectrum and the spatial and temporal resolution of remote sensing imaging have been improved continuously, which makes the image data of remote sensing sensors to be collected and transmitted to the ground rapidly. How to identify an object from the massive remote sensing image is a challenging and an urgent problem It is important research the visual function of human being and the process of human recognition and the physiological mechanism of human identification. According to the characteristics of the target, the object recognition preprocessing method is introduced, and the configuration result of target segmentation is given. For the different characteristics of several typical targets in the remote sensing image, the object segmentation technology proposed meets the preprocessing of multiclass typical remote sensing target segmentation [4] This method mainly uses the edge smoothing technology and the clustering segmentation technology, which are used for preprocessing objects with strong visual sense in the object-oriented segmentation. All kinds of remote sensing objects, such as airport, water, woodland, and residential area, converge to their respective color values, which lays a good foundation for subsequent object recognition [5]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
