High-resolution noctilucent remote sensing image automatic change detection method based on feature fusion

Abstract

The invention relates to a high-resolution noctilucent remote sensing image automatic change detection method based on feature fusion. The method comprises the following steps: 1), obtaining two-time-phase high-resolution noctilucent remote sensing data before and after a short-time major event in a research region, and carrying out the preprocessing of front and rear time-phase remote sensing images; 2) based on the preprocessed high-resolution noctilucent remote sensing data, extracting a plurality of derivative texture feature images, and superposing the derivative texture feature images toconstruct a multi-band feature image fused with texture features; 3) carrying out change detection on the multiband characteristic image in the step 2) by adopting a multivariate change detection algorithm MAD and an iterative weighting algorithm IR-MAD thereof to obtain a change intensity graph TMAD and a change intensity graph TIR-MAD fusing multiple characteristics; and 4) respectively segmenting the change intensity graphs TMAD and TIR-MAD to obtain respective corresponding binary change detection result graphs. Compared with the prior art, the method has the advantages of being suitablefor satellite-borne high-resolution LJ1-01 noctilucent remote sensing image processing, high in automation degree, high in precision, long in time sequence, large in monitoring range and the like.

Description

technical field [0001] The invention relates to the application field of multi-temporal high-resolution luminous remote sensing image change detection, in particular to an automatic change detection method for high-resolution luminous remote sensing images based on feature fusion. Background technique [0002] Short-term major events on the land surface are usually harmful, sudden, frequent, and very difficult to remedy. Once they occur, it will be difficult for emergency management personnel to predict and warn them. Early detection of short-duration major events through remote sensing is critical for the proper allocation of management resources. However, existing change detection methods may be expensive and time-consuming when applying change detection methods to the extraction and monitoring of short-term significant events. The biggest difference from traditional optical remote sensing images is that while nighttime light remote sensing images provide information abou...

AI Technical Summary

Problems solved by technology

However, it is limited to relatively rough and simple change detection through band calculation and manual setting of empirical thresholds, and the result verification only uses high-resolution images for qualitative verification, lacking quantitative accuracy evaluation basis

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