Neural network based sonar image super-resolution reconstruction method

Abstract

The invention discloses a neural network based sonar image super-resolution reconstruction method which is used for performing super-resolution reconstruction on a sonar image r to be reconstructed at super resolution. The method comprises the following steps of: performing nonsubsampled contourlet decomposition and neural network training on a high-resolution sonar image and four degraded sample images; performing cubic interpolation on the sonar image r to be reconstructed at super resolution and taking the interpolated image as a high-resolution low-pass sub-band coefficient; and performing nonsubsampled contourlet decomposition on the sonar image r again, inputting the sub-band coefficient of each band-pass direction of the sonar image r to be reconstructed at super resolution into a trained neural network to acquire the high-resolution sub-band coefficient of each band-pass direction, and finally performing nonsubsampled contourlet decomposition to acquire a super-resolution reconstructed sonar image R. The sonar image reconstructed at super resolution has a better edge, a detail keeping effect and a better visual effect and contributes to processing such as sea bottom survey, subsequent underwater target positioning and recognizing and the like.

Description

technical field [0001] The invention belongs to the technical field of image signal processing, and in particular relates to a neural network-based super-resolution reconstruction method for sonar images. Background technique [0002] The 21st century is the century for humans to explore and develop the ocean. The technical requirements for ocean surveying and naval defense construction are constantly improving, making underwater sonar technology more and more important. However, due to the variety of sounds in the ocean, the sonar images obtained by sonar equipment usually have low resolution, and the edges of targets are deteriorated, making it difficult to identify them. Effectively improving the resolution of sonar images and enhancing edge details will benefit seabed surveys and subsequent underwater target positioning and identification. [0003] The spatial resolution of an image is a measure of the ability to distinguish image details, and it is also a key indicator...

AI Technical Summary

Problems solved by technology

However, for sonar images with low resolution and blurred edge textures, most of the current super-resolution methods have problems such as blurred edges, less useful information, weak texture details, and low signal-to-noise ratio.

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