Sorting method and device for remote sensing images

Abstract

The invention discloses a sorting method and a sorting device for remote sensing images, and relates to the technology of image processing. According to the coverage condition of a target ground object, the remote sensing images are subjected to the partition of a distribution area of the target ground object to partition target ground object pure areas, target ground object mixed areas, and non-target ground object areas; the target ground object pure areas and the target ground object mixed areas are sorted by a hard sorting algorithm, and the target ground object mixed areas are sorted by a soft sorting algorithm; and sorting results of the areas are combined to form a sorting result of the remote sensing images. The pure areas and the mixing areas are sorted by the appropriate sortingmethod, so the sorting accuracy of the remote sensing images is improved. According to the sorting method, the problem of mixing pixels can be solved, the advantages of the conventional hard and softsorting methods are combined fully, and the sorting accuracy of the images is improved substantially.

Description

technical field [0001] The invention relates to image processing technology, in particular to a remote sensing image classification method and device. Background technique [0002] At present, remote sensing image classification is an important means to obtain internal information of remote sensing images. The purpose of remote sensing image classification is to divide each pixel in the image into different categories according to its spectral brightness, spatial structure characteristics or other information in different bands according to the set rules or algorithms. [0003] There are two traditional methods in remote sensing image classification, hard classification method and soft classification method. [0004] Hard classification method (hard classifications) is a pixel-level image classification method, which simply regards remote sensing images as composed of pure pixels in the classification process, and divides each pixel into a single land cover category. Hard ...

AI Technical Summary

Problems solved by technology

[0008] The main problem faced in the soft classification process is the inaccurate classification of pure target areas. Since the soft classification method decomposes all pixels in the image as mixed pixels in the entire classification process, the resulting classification results are It is expressed in the form of abundance, and also uses the form of percentage for the pixels in the pure area, so it is easy to cause classification errors

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