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Single-spectrum-driven double-category sparse representation hyperspectral image target detection method

A technology of hyperspectral image and sparse representation, which is applied in the field of target detection of two-category sparse representation hyperspectral images, can solve the problems of poor sparse vector effect and affect the detection effect, and achieve the effect of avoiding mutual influence and efficiently detecting targets.

Active Publication Date: 2019-12-17
WUHAN UNIV
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This method will make the two sparse vectors interact with each other, and the recovered sparse vector will be less effective, thus affecting the final detection effect

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  • Single-spectrum-driven double-category sparse representation hyperspectral image target detection method
  • Single-spectrum-driven double-category sparse representation hyperspectral image target detection method
  • Single-spectrum-driven double-category sparse representation hyperspectral image target detection method

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Embodiment Construction

[0015] In order to facilitate those skilled in the art to understand and implement the technical solution of the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. to limit the present invention.

[0016] The invention discloses a hyperspectral image object detection method driven by a single spectrum with a dual-category sparse representation. In the target dictionary construction part: use a given target spectrum as prior information, use the classic target detection operator for pre-detection, select the part of pixels with a larger output value in the initial detection statistics, and construct the target dictionary. In the background dictionary construction part: first use the principal component analysis method to reduce the dimensionality of the original hyperspectral image, and then use K-means clustering to classify the image; for each pixel category on the image, it is in t...

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Abstract

The invention discloses a single-spectrum-driven double-category sparse representation hyperspectral image target detection method, which comprises the following steps: constructing a target dictionary and a background dictionary, and taking a given target spectrum as prior information when the target dictionary is constructed; when a background dictionary is constructed, classifying and selectingpixels with high representation frequency in each category as background training samples to obtain a globally over-complete background dictionary; and as for the target dictionary and the backgrounddictionary, performing sparse representation on the pixels by using a double-category sparse representation model to obtain a target sparse vector and a background sparse vector, detecting the pixelsto be detected one by one, and extracting to obtain a target detection result of the hyperspectral remote sensing image X. According to the method, the background dictionary is a global background dictionary, so that all background ground object categories on the global image are well expressed; and the target category and the background category are separately subjected to sparse reconstructionin a double-category sparse representation mode, so that the separation of the target and the background in the hyperspectral image is efficiently realized, and the interested target is detected.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and in particular relates to a hyperspectral image target detection method driven by a single spectrum with a dual-category sparse representation. Background technique [0002] The rapid development of remote sensing earth observation technology and its application has changed the world mode of human cognition to a large extent, and it has become an important technical means to obtain surface information (Griffith, J..(1979). Remote sensing and image interpretation. John Wiley & Sons .). The value of remote sensing earth observation technology in practical applications depends to a large extent on whether the images obtained by satellite remote sensing can provide detailed and rich surface information. Compared with multispectral images, hyperspectral remote sensing images have the characteristics of large number of bands and extremely high spectral resolution. The spect...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/13G06V20/194G06F18/2136G06F18/241
Inventor 杜博朱德辉张良培
Owner WUHAN UNIV
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