A remote sensing image ship integrated recognition method based on deep learning

Abstract

The invention discloses a remote sensing image ship integrated recognition method based on deep learning. The method comprises the steps of image classification, target detection and image segmentation. Compared with the prior art, the method has the advantages that the modern artificial intelligence deep learning model is combined with the traditional image processing method to detect and segmentthe ship with the eye remote sensing image; The remote sensing image segmentation method based on deep learning can accurately identify ships in a sea area, is suitable for various processing environments, has a good anti-interference capability for a complex environment, and can accurately segment the detected and identified ships.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and relates to the specific fields of target detection and image segmentation, in particular to a deep learning-based remote sensing image ship integrated identification method. Background technique [0002] With the development of remote sensing information, the processing of remote sensing images gradually occupies an important position in the image field, and detection algorithms based on remote sensing images are emerging one after another. For the task of ship target detection and recognition in remote sensing images, most of the current detection algorithms use the traditional idea of ​​extracting features to detect target ships by applying preprocessing and enhancement techniques to the image. [0003] Due to the particularity of remote sensing images, compared with ordinary images, remote sensing images are easily affected by conditions such as illumination, weather, sea condition...

AI Technical Summary

Problems solved by technology

However, the objects processed by traditional segmentation methods are generally ordinary images. For remote sensing images with extremely complex environments, these segmentation algorithms can easily cause segmentation confusion, so that the foreground and background cannot be correctly segmented, and the segmented ships cannot be identified. Which type, it is naturally impossible to segment the ship target well

[0007] To sum up, the traditional target detection and image segmentation methods are unsatisfactory for the remote sensing images with rich information and complex conditions, and lack of adaptability to the processing environment.

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