Remote sensing image aircraft target detection method based on bounding box correction algorithm

Abstract

The invention provides a remote sensing image airplane target detection method based on a bounding box correction algorithm, and solves the problems that a traditional non-maximum suppression algorithm directly selects a bounding box with the highest score, and the detection bounding box is inaccurate, and a segmented airplane is marked by multiple boxes during detection, so that false alarm is caused. The method comprises the following steps: generating a training and testing sample set; preprocessing a training sample; overlapping and slicing the test samples to obtain preprocessed test samples; training an aircraft target detection model; detecting an aircraft target in the slice; carrying out bounding box correction on a detection result in the test sample by using a bounding box correction method; and generating an airplane target detection result graph. According to the invention, overlapping correction is carried out on the intersecting boundary frames on the same target by using an overlapping correction method, so that a more accurate detection frame is obtained. Fusion improvement is performed on the parallel adjacent boundary frames on the same target by using an adjacent fusion method, and multi-frame false alarms on the same target are removed in a detection result. The method is used for remote sensing image airplane target detection.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to aircraft target detection in the technical field of image target detection, in particular to an aircraft target detection method for remote sensing images based on a bounding box correction algorithm. The invention can be used for detecting aircraft targets in remote sensing images. Background technique [0002] In recent years, computer vision technology represented by target detection and recognition has made remarkable progress. Applying target detection technology to optical remote sensing images has become one of the research hotspots in remote sensing science and computer vision technology. [0003] Aircraft is a high-value military equipment and vehicle. Using target detection technology to automatically detect ground aircraft targets on remote sensing images is of great significance in both military and civilian fields. In the military field, timely and ef...

AI Technical Summary

Problems solved by technology

[0005]The traditional non-maximum suppression algorithm NMS method is based on the classification score, only the prediction frame with the highest score can be left, but in most cases the intersection and IoU It is not strongly correlated with the classification score, and many boxes with high confidence in the classification label are not very accurate

[0006]In addition, due to the segmentation of the remote sensing image, the aircraft target at the edge of the segmentation may be segmented, destroying the integrity of the aircraft target

At this time, in the target detection result, the detection frames will be marked on different positions of the same target. Since these frames are disjoint, that is, the Iou (intersection-over-union ratio) is zero, the traditional non-maximum suppression method cannot detect these same targets. The disjoint bounding boxes on the target are processed, which cannot solve the multi-frame false alarm problem caused by this situation

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