High-resolution remote sensing image segmentation method based on inter-scale mapping

Abstract

The invention discloses a high-resolution remote sensing image segmentation method based on inter-scale mapping. The high-resolution remote sensing image segmentation method has the advantages that aiming at geographical object extraction involved in objet-level change detection, the high-resolution remote sensing image multi-scale segmentation method based on wavelet transform and an improved JSEG (joint systems engineering group) algorithm is provided; aiming at a key problem that a conventional JSEG algorithm affects segmentation accuracy in high-resolution remote sensing image segmentation, a corresponding improvement strategy is adopted to achieve a good effect; wavelet transform is introduced to serve as a multi-scale analysis tool, excessive rough color quantization of the conventional JSEG algorithm is abandoned, and thus, detail information in original images is kept to the utmost; a novel inter-scale segmentation result mapping mechanism is set up, image segmentation of a current scale is realized on the basis of a segmentation result of a previous scale, and correction of the segmentation result of the previous scale is also realized, and thus, accumulation of inter-scale segmentation errors is decreased effectively; finally, an improved multi-scale segmentation strategy and an improved region merging strategy are provided, and over-segmentation and mistaken merging are effectively reduced.

Description

technical field [0001] The invention relates to a high-resolution remote sensing image segmentation method based on inter-scale mapping, and belongs to the technical field of remote sensing image segmentation. Background technique [0002] Compared with ordinary images, remote sensing images have the characteristics of multi-band, numerous types of ground objects, rich texture features, multi-scale, and wide coverage. First of all, remote sensing images usually contain data of multiple bands, which makes it difficult for traditional single-band image segmentation methods to be directly applied to multispectral or hyperspectral remote sensing image segmentation; in addition, remote sensing images usually contain rich texture information, which can be integrated Reflecting the complex spatial structure characteristics of various ground objects makes it more difficult to effectively extract and express the texture features of objects; moreover, remote sensing images usually cov...

AI Technical Summary

Problems solved by technology

[0006] In view of the inherent limitations of the JSEG algorithm and the difficulties caused by high-resolution remote sensing images, especially in urban scenes

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