Water sky line detection method based on gradient saliency

Abstract

The invention relates to a water sky line detection method based on gradient saliency. The method comprises steps as follows: a frame image is acquired by an optical imaging instrument, and if the image is a color image acquired by an ordinary camera, the image is subjected to standardization processing, and a 24-bit RGB (red green blue) color image is obtained; if the image is a gray image acquired by an infrared imaging instrument, the image is subjected to standardization processing, and an 8-bit gray image is obtained; the obtained standardized image is subjected to Gaussian downsampling and the like. A gradient magnitude matrix and a gradient direction matrix of the image are calculated respectively according to the type of the image acquired by the optical imaging instrument, all gradient information of an original image is reflected in the result, and accuracy of the water sky line detection result is guaranteed. Line segment detection based on a region growing algorithm is performed sequentially from high to low according to the gradient saliency, and the problem of severe noise interference due to the fact that gradient information is directly used for detection is solved.

Description

technical field [0001] The invention relates to a water antenna detection method based on gradient saliency. Background technique [0002] In recent years, with the introduction of the concept of unmanned ships and the development of surface unmanned boat technology, the future maritime transportation mode and ocean observation technology are facing major changes, which will have a great impact on my country's marine science research, national economic development and social development. Progress has important and far-reaching consequences. According to the application requirements in the actual marine environment, unmanned ships and surface unmanned boats need to be equipped with various types of sensors such as radar, optical imaging equipment, and sonar to obtain information and data of the environment, targets, and obstacles within a certain range. And independently complete information understanding behaviors such as detection, tracking, and identification, so as to hav...

AI Technical Summary

Problems solved by technology

However, in the optical image under the actual sea surface environment, there is often strong background interference formed by cloud radiation and sea surface wave reflection, and the changeable meteorological conditions on the sea surface (such as rain, snow, fog, etc.) will seriously reduce the clarity and contrast of the image. And form noise interference, so it is very difficult to realize the accurate detection of water antenna

According to the different characteristics of the sea surface area and the sky area, a water antenna detection method based on the maximum inter-class variance is proposed in the document "Automatic detection method of infrared small targets in complex sea background", but this method will completely fail when there is strong background interference in the image

"Research on Water Antenna Extraction Algorithm Based on Wavelet Transform" proposed a water antenna detection method based on wavelet analysis, but it is difficult to determine the scale of wavelet type selection and decomposition, and has the disadvantage of poor real-time performance

"A real time sea sky line detection method under complicated sea-sky background" determines the candidate points of the water antenna according to the maximum variance criterion in the area, and then combines the Ransac algorithm to fit the water antenna, but this method is easily affected by background interference

"Research on Robust Sea Antenna Detection Algorithm under Complex Sea and Air Background" uses the directional gradient operator to obtain the difference image, and then uses the Hough transform to detect the position of the water antenna, but this method will produce large errors when the image contrast is low or the noise is serious

A comprehensive analysis of relevant literature shows that the existing water antenna detection methods cannot meet the real-time, accuracy, robustness, and reliability requirements of applications in complex sea surface environments.

Images