A method for detecting automatically a circular oil tank with a remote sensing image

Abstract

The invention discloses a method for detecting automatically a circular oil tank with a remote sensing image. The method comprises: first, executing MHC visual saliency transformation on the remote sensing image to obtain a visual saliency map, executing mathematical morphology enhancement to obtain a enhanced visual saliency map, and executing circle detection on the enhanced visual saliency map by means of hough transformation to obtain a suspected oil tank region; then, executing turbopixels over-segmentation on the remote sensing image, combining segmented blocks according to features, and obtaining a suspected oil tank region according to an approximately-circular feature; last, in conjunction with a hough detection result and an approximately-circular feature detection result, executing SVM classification by means of a relationship between a circle center and a radius of the oil tank and multiple features, and filtering out concentric circles and a non-oil tank region to obtain finally an oil tank region. Through a large number of experiments, it is proved that the method for detecting automatically a circular oil tank with a remote sensing image can obtain the higher precision ratio and recall ratio on the optical image having a large region and high resolution, and not only have a significant detection effect on the bright oil tank, but also have a certain detection effect on the darker oil tank.

Description

technical field [0001] The invention belongs to the technical field of high-resolution optical remote sensing image target recognition, and in particular relates to an automatic detection method for circular oil tanks in remote sensing images based on the combination of over-segmentation plus multi-feature detection and Hough circle detection on saliency maps. Background technique [0002] Fuel depots have always been of great importance for military and civilian applications. In terms of civil use, in the extraction and analysis of damage information of airport remote sensing images, the accuracy of oil tank identification and detection directly affects the effect of damage information extraction and analysis; in the military, oil depots are used as storage facilities for crude oil and refined oil and other materials , plays an important role in the strategy, and an effective attack on the enemy's oil depot target can often destroy the enemy's strategic deployment, greatly ...

AI Technical Summary

Problems solved by technology

[0006] It can be seen that various algorithms are still limited by many conditions, such as image background interference, target size, illumination changes, etc. For high-resolution remote sensing images, oil tank targets are small targets, some are regular, and some are messy The probability of missing alarms and false alarms in the detection process is relatively high

At the same time, under normal circumstances, visible light images will be affected by clouds, the background of the oil tanks is different, it is difficult to establish a background model, the color of the oil tanks is different, the difference between the target and the background in the image of each region is inconsistent, and the contrast with the background is not the same , especially for black polar oil tanks, which are similar to the background and difficult to distinguish

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