A Nonlinear Enhancement Method for Side Scan Sonar Images

Abstract

The invention belongs to the technical field of side-scan sonar image processing, and in particular relates to a nonlinear enhancement method for side-scan sonar images. The present invention comprises the following steps: obtaining the original image from the original side-scan sonar data file, then sequentially performing gray scale normalization, neighborhood extremum suppression and Gaussian smoothing on the original image, and then calculating the low gray scale area for the smoothed image The maximum value, the minimum value of the high gray area and the middle gray area, and finally perform nonlinear correction on the above three areas respectively to obtain the enhanced image. Through the above steps, the present invention can realize the enhancement of effective signals and the suppression of invalid signals of the original side-scan sonar image quickly, effectively and at low cost, enhance the contrast of local features of the image, and maintain the monotony of the edge and gray distribution of the original image Sex, do not quote false edges, etc.

Description

technical field [0001] The invention belongs to the technical field of side-scan sonar image processing, and in particular relates to a nonlinear enhancement method for side-scan sonar images. Background technique [0002] With the development of science and technology in all countries in the world, the exploration of the marine environment and the development and utilization of seabed resources are one of the key technologies for countries to improve their comprehensive strength. Due to the good transmission performance of sound waves in water media, sonar imaging technology is widely used in deep-sea long-distance detection, but because of the low contrast and blurred edges of the original side-scan sonar image, the original sonar image cannot be directly used for feature detection. In post-processing such as detection and target recognition, it is necessary to enhance the original side-scan sonar image. [0003] Side scan sonar image enhancement can be divided into two c...

AI Technical Summary

Problems solved by technology

Commonly used spatial domain-based correction methods include average grayscale correction, histogram correction, and gamma correction. These methods have the advantage of fast speed. However, these methods will amplify noise while enhancing grayscale, and even destroy the original image. Edge and feature distribution, leading to poor image quality

Commonly used correction methods based on the frequency domain include Curvelet transform and wavelet transform. Although these methods have good effects on feature enhancement, edge preservation and noise suppression, they will consume a lot of time and cannot guarantee the accuracy of the subsequent correction. real-time processing

According to the imaging principle of side scan sonar, the gray scale of side scan sonar image can be divided into low gray scale area, intermediate gray scale area and high gray scale area. In the invalid signal area of ​​noise, the high gray area is the area with relatively strong reflection waves, and the middle gray area is mostly the reflection area of ​​the background. At present, there is no side scan sonar image enhancement that operates on the gray distribution characteristics of the above three areas. method

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