Change Detection Method of Remote Sensing Image Based on Local Entropy Visual Attention Model

Abstract

The invention discloses a method for detecting changes of a remote sensing image of a visual attention model based on local entropy, and mainly aims to solve the problem about the high omission factor in change detection in the prior art. The method comprises the following steps: first, extracting gray feature and direction feature of the remote sensing image before and after the change respectively and acquiring feature images of the image before and after the change in all feature space; second, constructing a front gaussian pyramid and a rear gaussian pyramid by using the feature images before and after the change, performing 'center-D-value' operation between the front gaussian pyramid and the rear gaussian pyramid, and acquiring the feature images in all feature space; third, calculating local entropies of the feature images in different feature space respectively, performing weight fusion on the feature images adding entropy in different feature space, and acquiring saliency maps of the visual attention model; and finally, classifying the saliency maps by using the fuzzy C-means method and acquiring the final change detection result image. The method, disclosed by the invention, avoids the problems about information loss and accumulative error in the prior art and improves the detection precision of change detection.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to the processing of remote sensing images, which can be mainly applied to the monitoring of ecology and environment and the evaluation and prevention of natural disasters. Background technique [0002] Remote sensing image change detection refers to the technology of selecting appropriate detection methods, extracting and analyzing change information from multiple remote sensing images acquired in different periods, and generating change distribution maps and other detection results. At present, remote sensing image change detection technology change detection has become a research focus of remote sensing image processing research, and is widely used in various fields of social economy, such as disaster monitoring and assessment, land use analysis, water resource quality and geographical distribution investigation. , urban planning and layout, climate change monitoring, ba...

AI Technical Summary

Problems solved by technology

[0004] The main defects of the current change detection method are as follows: for the direct image comparison method, firstly, the separability of the difference map directly affects the change detection results, and the construction of a high-separability difference map has been a difficult problem so far; secondly, the simple The direct image comparison method of the traditional image neither utilizes the spatial information of the image, nor considers the influence of noise or illumination changes, and it is easy to cause false detection or false detection; finally, in the process of constructing the difference map, it is inevitable to cause The loss of image information, the direct image comparison method compresses the change information to the one-dimensional difference image, and loses the band information of the remote sensing image, thus making the detection inaccurate

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