High-resolution remote sensing target extraction method based on multi-scale semantic model

A technology for object extraction and semantic modeling, used in character and pattern recognition, instruments, computer parts, etc.

Active Publication Date: 2012-12-05
济钢防务技术有限公司
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AI Technical Summary

Problems solved by technology

The invention solves the problem of how to comprehensively utilize the multi-scale segmentation of images and the semantic model of target categories to automatically extract objects and objects in high-resolution remote sensing images

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  • High-resolution remote sensing target extraction method based on multi-scale semantic model
  • High-resolution remote sensing target extraction method based on multi-scale semantic model
  • High-resolution remote sensing target extraction method based on multi-scale semantic model

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Embodiment Construction

[0063] Below in conjunction with embodiment and accompanying drawing, the method of the present invention is further described.

[0064] figure 1 It is a schematic flow chart of the high-resolution remote sensing target extraction method based on the multi-scale semantic model of the present invention, and the specific steps include:

[0065] The first step is to establish a set of candidate regions for high-resolution remote sensing objects:

[0066] The pictures in the remote sensing man-made object data set are intercepted from Google Earth. The resolution of these images is around 1 meter. Consists of 200 images. The average size of the images is approximately 200x200 pixels. Such as image 3 shown. For each class of target images, 130 of them are used for training and 70 for testing.

[0067] Multi-scale segmentation of training images: Use the Normalized-cut algorithm to segment each training image according to a given scale and number of segmentation blocks. Con...

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Abstract

The invention discloses a high-resolution remote sensing target extraction method based on a multi-scale semantic model, and relates to a remote sensing image technology. The high-resolution remote sensing target extraction method comprises the following steps of: establishing a high-resolution remote sensing ground object target image data set; performing multi-scale segmentation on images in a training set, and obtaining a candidate image area block of the target; establishing a semantic model of the target, and calculating the implied category semantic features of the target; performing semantic feature analysis on candidate image blocks on all levels; and finally, calculating a semantic correlation coefficient of the candidate area and the target model, and extracting the target through maximizing semantic correlation coefficient. By the method, the target in the high-resolution remote sensing image is extracted by comprehensively utilizing the multi-scale image segmentation and target category semantic information; the method is accurate in extraction result, high in robustness and applicability, and has a certain practical value in the construction of the geographic information system and digital earth system; and the manual involvement degree is reduced.

Description

technical field [0001] The invention relates to a method for target extraction in the field of remote sensing image information processing, especially a method for extracting ground objects in high-resolution remote sensing images by constructing a semantic model of the target, which is a comprehensive utilization of multi-scale images A method of extracting ground objects and targets from high-resolution remote sensing images using information and target category semantic models. Background technique [0002] The resolution in high-resolution remote sensing images refers to the spatial resolution, and its measurement method is the size of the ground area corresponding to the unit pixel. The main satellite remote sensing data sources in the 1980s and 1990s were Landsat and Spot satellite data with a resolution of 10-30m, which can only be called medium-resolution images now. The successful launch of Ikonos in 1999 and QuickBird in 2001 improved the spatial resolution of rem...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46
Inventor 李宇孙显王宏琦
Owner 济钢防务技术有限公司
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