Remote sensing image region-of-interest detection method based on multi-significant-feature fusion

Abstract

The present invention discloses a remote sensing image region-of-interest detection method based on multi-significant-feature fusion, belonging to the technical fields of remote sensing image processing and image identification. The remote sensing image region-of-interest detection method comprises the following steps: 1) obtaining color channels of one group of input remote sensing images and calculating a color histogram of each color channel; 2) calculating a standard significant weight of each color channel according to the color histograms; 3) calculating an information content significant feature image; 4) converting one group of input remote sensing images from an RGB color space to a CIE Lab color space; 5) utilizing a clustering algorithm to obtain clusters; 6) calculating a significant value of each cluster, and obtaining a common significant feature image; 7) fusing the information content significant feature image with the common significant feature image to obtain a final significant image; and 8) performing threshold segmentation through an OTSU method to extract a region of interest. Compared with a traditional method, the remote sensing image region-of-interest detection method of the present invention achieves accurate detection for a remote sensing image region-of-interest on the premise of not having a prior knowledge base, thus the remote sensing image region-of-interest detection method can be widely applied to fields such as environment monitoring, land utilization and agricultural investigation.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing and image recognition, and in particular relates to a method for detecting a region of interest in a remote sensing image based on fusion of multiple salient features. Background technique [0002] With the rapid development of remote sensing technology, the data scale of remote sensing images is rapidly expanding, and the extraction of regions of interest in remote sensing images can reduce the complexity of remote sensing image analysis and processing, so the extraction of regions of interest in remote sensing images is also a hot spot of attention recently. How to accurately and quickly realize the detection of regions of interest in remote sensing images has become one of the problems to be solved urgently. An effective solution to this problem will be of great significance for alleviating the contradiction between high-speed acquisition and low-speed interpretation of ...

AI Technical Summary

Problems solved by technology

However, the establishment of a priori knowledge base itself is a very complicated problem, which needs to comprehensively consider information such as expert knowledge base, target area characteristics, background area characteristics, etc.

Images