Front-scan sonar image splicing method

Abstract

The invention relates to a front-scan sonar image splicing method, which comprises the following steps of: matching feature points between a reference sonar image and a sonar image to be matched in a frame adjacent to the reference sonar image according to a speeded up robust feature (SUFR) algorithm; estimating and calculating a homograph matrix between the reference sonar image and the sonar image to be matched through a transformation model, mapping the feature points of the sonar image to be matched to a coordinate system of the reference sonar image one by one, and accurately matching the reference image and the sonar image to be matched through image interpolation; and continuously repeating the steps to accurately match all the sonar images in a sonar sequence, and splicing the sonar images through brightness adjustment and image fusion. According to the method, the problems of low sonar image resolution and small detection range visual angle of dual-frequency identification sonar (DIDSON) during underwater monitoring are solved; and due to sonar image splicing, a series of sonar images are spliced into a sonar image with high resolution and large range, so that an underwater environment with a relatively large range can be monitored by DIDSON.

Description

technical field [0001] The invention relates to a method for mosaicing forward-scan sonar images, which can stitch forward-scan sonar images with smaller viewing angles into a high-resolution and wide-range image. Background technique [0002] At present, countries all over the world are committed to using underwater unmanned detectors to conduct research on the underwater acoustic environment and target detection of water resources such as oceans, lakes, and rivers. This underwater moving target detection technology not only has potential huge economic benefits in civilian aspects such as ocean development and port channel construction, but also has important significance in safety detection such as underwater environment monitoring. [0003] Due to the great commercial and military value of underwater robots and the many technical challenges they face, more and more scientists and technicians have paid more and more attention to their technical research, and a lot of work ...

AI Technical Summary

Problems solved by technology

Due to the complexity of the working environment, the high-resolution dual-frequency identification sonar has the following difficulties in performing underwater dangerous target detection tasks: 1) The real-time interpretation of sonar images still relies on human eyes to manually detect Interpret and identify suspicious underwater targets. However, the principle of acoustic imaging is completely different from that of optical imaging, especially its resolution is much smaller than that of optical imaging. Therefore, it is very difficult to detect and identify dangerous targets like underwater suspicious explosives, and Interpreters are very hard-working and easily fatigued; 2) The high-resolution sonar itself has a narrow field of view, which requires image stitching; 3) When the sonar equipment works underwater, it will be affected by surges and currents, resulting in pitch, Rolling, which causes distortion of the sonar image

In practical applications, DIDSON can only observe images within a small viewing angle range at the same time

Images