Remote sensing image ship detection method based on block extraction

Abstract

The invention discloses an optical remote sensing image ship detection method based on block extraction of interest, and mainly solves the problems of low detection precision and more false alarms inthe prior art. The method comprises the following steps: constructing an optical remote sensing image ship detection data set; carrying out downsampling and defogging enhancement on the wide remote sensing image, and carrying out land and water segmentation by using context information and image global features; training an SCRDet-based target detection model by using the constructed data set; according to the land and water segmentation result, scanning the original wide remote sensing image by using a partially overlapped sliding window to extract an interested block as a to-be-detected area, and inputting the to-be-detected area image into the detection model to obtain an area detection result; mapping a region result to an original wide image scale, and performing improved non-maximumsuppression to optimize a preliminary detection result; and optimizing the detection result again according to the structural characteristics of the ship. The method is high in detection precision and low in false alarm rate, and can be used for acquiring ship targets of interest and positions thereof in large-format remote sensing images.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to an optical remote sensing image ship detection method, which can be used for target recognition in large format remote sensing images. Background technique [0002] Target detection of optical remote sensing images is one of the important issues in the field of remote sensing image research, and ship target detection has extremely important application value in fishery management, military reconnaissance and strategic deployment due to its particularity and criticality. Ship target detection is to determine whether there is a ship in the water or on the shore from a complex scene, and to locate it. [0003] Traditional ship target detection methods mainly include methods of using sea and land segmentation and using prior geographic information. The adaptability is not strong when the target is detected simultaneously. [0004] In recent years, deep learning has develop...

AI Technical Summary

Problems solved by technology

However, the method based on deep learning does not segment the image into water and land, but directly inputs the wide image slice into the trained model to generate the result. Inputting the complex land area that does not contain water into the detection model not only reduces the detection efficiency, but also It may cause obvious false alarms on land. In addition, the hull incompleteness caused by the segmented image will also cause obvious missed detection, so the detection accuracy is not high.

Images