Adaptive extraction method of remote sensing image thematic information based on spectrum matching degree

Abstract

The invention provides an adaptive extraction method of remote sensing image thematic information based on spectrum matching degree. The method comprises the following steps: firstly, artificially selecting a sample region of a thematic ground object, carrying out PPI calculation in the sample region, selecting pixels with maximum purity as end members of the thematic ground object, extracting spectrums of the end members, and subsequently, utilizing whole matching degree indexes which integrate the similarity of distances and shapes among the spectrums to calculate the matching degree of the spectrums between the pixels and the end members on an image; secondly, adaptively determining the segmentation threshold of a spectrum matching degree image by using an image histogram automatic segmentation method, so as to obtain initial separation of the thematic ground object and the whole background; and next, carrying out statistic segmentation on the gray level mean value and standard deviation of thematic ground object pixels, adaptively determining the threshold of region growth, traversing the thematic ground object pixels and taking the thematic ground object pixels as seed points to carry out region growth; and finally, in a grown thematic ground object local unit, adopting an iteration method to carry out adaptive local classification to continuously approach a real thematic ground object boundary, thereby obtaining a final refined ground object extraction result.

Description

technical field [0001] The invention relates to a method for self-adaptive extraction of topical information from remote sensing images based on spectral matching degree, which uses image endmember selection, spectral matching, automatic image segmentation, "whole-partial" space conversion, region growth and local iterative algorithms to realize topical information. The self-adaptive and refined extraction of information belongs to the field of computer image processing, especially the field of remote sensing information extraction technology, and can be widely used in many fields such as environment, agriculture, and forestry. Background technique [0002] Thematic information extraction of remote sensing images is a key link in the application of remote sensing image data to industry practice, and it has always been one of the key points and hot spots in the field of remote sensing research. In addition, remote sensing imaging itself is a comprehensive and complex process,...

AI Technical Summary

Problems solved by technology

[0003] However, regardless of the classification or spectral matching method, a unified model is used when extracting thematic information, which often leads to omission and wrong extraction of thematic features due to the interference of other features; Too much manual intervention and the addition of background knowledge; Insufficient consideration of the spatial distribution characteristics of thematic features

In addition, the existing spectral library data types are limited, and it is difficult to apply spectral feature matching methods to different regions

Therefore, the existing methods are still relatively deficient in terms of universality, process and automation, and new algorithms need to be studied

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