A hyperspectral target detection method based on conditional random projection

A conditional random and target detection technology, applied in the field of remote sensing image processing, can solve the problems of wide range of negative samples, unreasonable extraction and matching process, etc., to achieve the effect of improving sensitivity, high test operation efficiency and improving accuracy.

Active Publication Date: 2019-05-21
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

In the hyperspectral target spectral detection task, the target spectral data is clear, but the category of negative samples is too wide, and...

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  • A hyperspectral target detection method based on conditional random projection
  • A hyperspectral target detection method based on conditional random projection
  • A hyperspectral target detection method based on conditional random projection

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[0036] The present invention will be described in detail below with reference to the accompanying drawings and examples. The flow chart of this embodiment is as follows figure 1 shown, including the following steps:

[0037] Step 1. Collect the spectral vectors of the images to be processed to form a training set and normalize them to obtain sample spectral data and their corresponding labels; the sample spectral data includes positive sample data and negative sample data;

[0038] The specific process is: for the image to be processed acquired by the same hyperspectral detector, the spectral vector corresponding to each pixel in the spatial dimension is extracted, and divided into spectral data including the target (positive sample) and the background (negative sample) and mark it. The marked spectral vectors are divided into training set and test set according to the required ratio, and the schematic diagram of the positive sample generative feature description and feature...

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Abstract

The invention provides a hyperspectral target detection method based on conditional random projection characteristics, which can realize accurate and rapid detection of a target and can improve the sensitivity to the number of training samples. The invention provides a supervised feature selection and feature extraction method based on conditional random projection in the aspect of characterization of hyperspectral image spectral data. A projection parameter matrix related to data and labels is obtained, and conditional random characteristics are obtained through the projection parameter matrix, so that the accuracy of target detection is improved; Meanwhile, screening estimation and sampling are added in the whole operation solving process; that the time for screening estimation and sampling operation is less, the training time is short, the screening estimation and sampling operation is completed in an offline stage, and a result obtained by training is directly used during actual operation, so that the method has the advantages of high detection accuracy and high test operation efficiency.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and relates to a hyperspectral remote sensing target rapid detection method based on a conditional random projection feature extraction strategy. Background technique [0002] With the rapid development of hyperspectral remote sensing technology, hyperspectral applications in military affairs and people's livelihood are becoming more and more extensive, which leads to higher and higher requirements for hyperspectral data processing for specific application environments. Among them, the detection of typical ground objects and targets in hyperspectral remote sensing images is an important research direction, which is of great significance in the scientificity of urban configuration, agricultural planting distribution planning, and military sensitive target classification and extraction. [0003] At present, in the field of typical target detection of hyperspectral objects, t...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
Inventor 唐林波周士超邓宸伟王文正赵保军
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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