Hyperspectral anomaly detection method and device

Abstract

The invention relates to a hyperspectral anomaly detection method and apparatus. The method comprises the steps of obtaining hyperspectral data of an object row by row; calculating a minimum row number k of the hyperspectral data required for determining background information; if a row mark number of a current row of the obtained hyperspectral data is greater than k, calculating an autocorrelation matrix of the current row of the hyperspectral data, taking the autocorrelation matrix as a first autocorrelation matrix, and taking a background autocorrelation matrix of all rows of the hyperspectral data before the current row as a second autocorrelation matrix; calculating a background autocorrelation matrix of the current row of the hyperspectral data and all the rows of the hyperspectral data obtained before the current row of the hyperspectral data; performing compression processing on the background autocorrelation matrix to obtain a compressed matrix; and performing anomaly detection on the current row of the hyperspectral data by utilizing the compressed matrix. According to the method and the apparatus, the anomaly detection is carried out row by row, so that the processing efficiency is improved, and the demands of special industries on real-time or quasi real-time processing of the hyperspectral data can be met.

Description

technical field [0001] The invention relates to the technical field of remote sensing, in particular to a hyperspectral anomaly detection method and device. Background technique [0002] At present, hyperspectral image data has the characteristics of map-spectrum integration, that is, the spatial information and spectral information of the target can be observed at the same time, which provides an effective remote sensing technology for target classification and recognition. [0003] However, there are many bands of hyperspectral images, and when detecting anomalies, the entire image is generally processed once and for all after receiving all hyperspectral image data, so the data processing process is complicated and inefficient, and it is difficult to meet the needs of special industries. The need for real-time or quasi-real-time processing of hyperspectral data. Contents of the invention [0004] In view of the above defects, the present invention provides a hyperspectr...

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Problems solved by technology

[0003] However, there are many bands of hyperspectral images, and when detecting anomalies, the entire image is generally processed once and for all after receiving all hyperspectral image data, so the data processing process is complicated and inefficient, and it is difficult to meet the needs of special industries. Demand for real-time or quasi-real-time processing of hyperspectral data

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