English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In the field of deep-sea exploration, sonar is presently the only efficientlong-distance sensing device. The complicated underwater environment, such asnoise interference, low target intensity or background dynamics, has broughtmany negative effects on sonar imaging. Among them, the problem of nonlinearintensity is extremely prevalent. It is also known as the anisotropy ofacoustic sensor imaging, that is, when autonomous underwater vehicles (AUVs)carry sonar to detect the same target from different angles, the intensityvariation between image pairs is sometimes very large, which makes thetraditional matching algorithm almost ineffective. However, image matching isthe basis of comprehensive tasks such as navigation, positioning, and mapping.Therefore, it is very valuable to obtain robust and accurate matching results.This paper proposes a combined matching method based on phase information anddeep convolution features. It has two outstanding advantages: one is that thedeep convolution features could be used to measure the similarity of the localand global positions of the sonar image; the other is that local featurematching could be performed at the key target position of the sonar image. Thismethod does not need complex manual designs, and completes the matching task ofnonlinear intensity sonar images in a close end-to-end manner. Feature matchingexperiments are carried out on the deep-sea sonar images captured by AUVs, andthe results show that our proposal has preeminent matching accuracy androbustness.

Nonlinear Intensity Underwater Sonar Image Matching Method Based on Phase Information and Deep Convolution Features