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Neighbor point searching method and system for spectral image dimensionality reduction

A spectral image and data dimensionality reduction technology, applied in the field of spectral image data dimensionality reduction, can solve the problem that the data cannot reconstruct the three-dimensional characteristics of hyperspectral data well, so as to reduce redundancy, improve robustness, and improve performance effect

Active Publication Date: 2015-01-07
WUHAN UNIV
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Problems solved by technology

This regards the spectral image as an isolated point, or a group of disordered spectral vector queues, ignoring the spatial information in the spectral image, so that the data after dimensionality reduction cannot reconstruct the hyperspectral data well. Three-dimensional characteristics

Method used

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  • Neighbor point searching method and system for spectral image dimensionality reduction
  • Neighbor point searching method and system for spectral image dimensionality reduction
  • Neighbor point searching method and system for spectral image dimensionality reduction

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Embodiment

[0046] The concrete operation of embodiment is as follows:

[0047] like figure 2 , take the current pixel as the center, take a window of 3×3 size, N=9, and set each pixel in the window from left to right and from top to bottom to be X 1 ,X 2 ,X 3 ,X 4 ,X 5 ,X 6 ,X 7 ,X 8 ,X 9 , where X 5 is the current pixel; calculate X separately 1 ,X 2 ,X 3 ,X 4 ,X 5 ,X 6 ,X 7 ,X 8 ,X 9 with X 5 The spectral distance, the spectral distance calculation formula is as follows:

[0048] SAM ( a , b ) = cos - 1 a , b > | a | | b |

[0049] Among them, SAM(a,b) is the spectral distance between pixel a and pixel b...

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Abstract

The invention provides a neighbor point searching method and system for spectral image dimensionality reduction. The method includes the steps of screening pixels of a window where current pixels are located and eliminating the pixels greatly interfered by noise and other factors; sequencing the current pixels and pixels in a window where pixels to be compared are located, and calculating the spectral distance between the current pixels and the window where the pixels to be compared are located; selecting multiple pixels with the highest similarity as neighbor points of the current pixels. According to the method, spatial information is fully used, a searching process is not influenced by changes of geometrical morphology of images through sequencing, spatial robustness is achieved, some noise pollution points are well prevented, the found neighbor points are more accurate, and data dimensionality reduction performance of hyperspectral images is improved.

Description

technical field [0001] The present invention relates to the technical field of spectral image data dimensionality reduction, in particular, the present invention relates to a neighbor point search method and system for spectral image data dimensionality reduction. Background technique [0002] Spectral remote sensing is a new technology for earth observation. It is a technique for obtaining spectral data in many fine and continuous narrow bands in the ultraviolet, visible, near-infrared, mid-infrared and thermal infrared bands of the electromagnetic spectrum. Using airborne or spaceborne instruments with high spectral resolution, remote sensing of the earth's surface can obtain a lot of information that is difficult to obtain from ground observations. What the spectral imager obtains is a three-dimensional data cube, which includes two-dimensional spatial information and one-dimensional spectral curve information of each pixel. With the advancement of spectrometer technolog...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06T3/06
Inventor 黄珺马泳马佳义
Owner WUHAN UNIV
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