Hierarchical detection method of specific artificial region using local structural constraint in remote sensing images

Abstract

Automatic detection of specific artificial region is one of the research hotspots in remote sensing image. In this study, a hierarchical detection method of specific artificial region using local structure constraint in remote sensing images is proposed. The process can be divided into two main stages: screening of keypoints based on the description of structural pattern, and specific artificial regions detection based on the local structural similarity. This method can greatly reduce the calculation of feature description in the redundant non-specific regions, and effectively reduce the error matching points to achieve the rapid and reliable detection of the specific artificial region. The authors test the proposed method on the artificial region sets with different types and time phase. The experimental results show that the method has high computational efficiency and detection accuracy.

Keywords

• geophysical image processing
• edge detection
• feature extraction
• object detection
• remote sensing
• image matching
• specific artificial region
• local structure constraint
• remote sensing image
• specific artificial regions detection
• local structural similarity
• redundant nonspecific regions
• artificial region sets
• hierarchical detection method
• local structural constraint