Change Detection Method of Remote Sensing Image Based on Treelet Image Fusion

Abstract

The invention discloses a Treelet image fusion-based remote sensing image change detection method which manly solves the problems in the prior art that the noise suppression capacity of a difference method is poor and detail information such as edges is not kept well by a logarithm ratio method. The Treelet image fusion-based remote sensing image change detection method is realized by comprising the steps of: extracting four different charts of an image before and after change by using different methods; then carrying out dimension reduction on a matrix image formed by the four difference charts by using Treelet, wherein data of each difference chart is used as one dimension of data to be subjected to dimension reduction during dimension reduction; and finally, carrying out clustering and segmenting on data subjected to dimension reduction by using an FCM (Fuzzy C-Mean) clustering algorithm to obtain a change detection result. The Treelet image fusion-based remote sensing image change detection method has the advantages of overcoming the defects of sensitivity of difference charts to noise and marginal information loss of a ratio diaphragm, reducing error rate and well storing detail information, and can be used in dynamic monitoring of forest sources, change detection of soil coverage and utilization and natural disaster evaluation of forest resources.

Description

technical field [0001] The invention belongs to the technical field of image processing, and is mainly applied in the field of remote sensing image change detection, that is, to detect changes in the ground surface according to remote sensing images of different time phases, and is mainly applicable to ground object coverage and utilization, natural disaster monitoring, and urban planning , map updates to military areas, etc. Background technique [0002] The change detection of remote sensing images refers to detecting the change information of the ground features in the area over time by analyzing two or more remote sensing images from the same area at different times. Change detection in remote sensing images has been widely used in dynamic monitoring of forest resources, monitoring of changes in land cover and utilization, urban planning layout, environmental monitoring analysis, natural disaster assessment, and man-made target monitoring and ground armed deployment anal...

AI Technical Summary

Problems solved by technology

The image difference method is very sensitive to the change area of ​​the remote sensing image, which is conducive to retaining the geometric edge of the change information, so as to accurately extract the change area, but due to the influence of the noise of the remote sensing image, the difference method is not suitable for analyzing Larger Remote Sensing Images

The image logarithmic ratio can effectively suppress the noise of the remote sensing image, but it will cause a certain blur to the edge of the change area, especially for images with a large number of weak changes and small area change information, this method is not conducive to the outline of the change area. and maintenance of details

Images