Double-scattering approximation for the bathymetry problem

Kan, V. A.; Sushchenko, A. A.; Lyu, E. R.

doi:10.1117/12.2540982

Cited by 1 publication

(1 citation statement)

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“…The spatial domain method aims to directly act on the sonar-scattered signal and compare it to the gray value. Such methods include Brightness Preserving Dynamic Histogram Equalization (BPDHE) [11], unsharpened masks [12], partial differential equation enhancement (PDEE) [13], etc. The BPDHE model improves the global contrast of images, but its correction and improvement capabilities are limited.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Scale Fusion Strategy for Side Scan Sonar Image Correction to Improve Low Contrast and Noise Interference

Zhou,

Chen,

Tang

et al. 2024

Remote Sensing

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Side scan sonar images have great application prospects in underwater surveys, target detection, and engineering activities. However, the acquired sonar images exhibit low illumination, scattered noise, distorted outlines, and unclear edge textures due to the complicated undersea environment and intrinsic device flaws. Hence, this paper proposes a multi-scale fusion strategy for side scan sonar (SSS) image correction to improve the low contrast and noise interference. Initially, an SSS image was decomposed into low and high frequency sub-bands via the non-subsampled shearlet transform (NSST). Then, modified multi-scale retinex (MMSR) was employed to enhance the contrast of the low frequency sub-band. Next, sparse dictionary learning (SDL) was utilized to eliminate high frequency noise. Finally, the process of NSST reconstruction was completed by fusing the emerging low and high frequency sub-band images to generate a new sonar image. The experimental results demonstrate that the target features, underwater terrain, and edge contours could be clearly displayed in the image corrected by the multi-scale fusion strategy when compared to eight correction techniques: BPDHE, MSRCR, NPE, ALTM, LIME, FE, WT, and TVRLRA. Effective control was achieved over the speckle noise of the sonar image. Furthermore, the AG, STD, and E values illustrated the delicacy and contrast of the corrected images processed by the proposed strategy. The PSNR value revealed that the proposed strategy outperformed the advanced TVRLRA technology in terms of filtering performance by at least 8.8%. It can provide sonar imagery that is appropriate for various circumstances.

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Section: Introductionmentioning

confidence: 99%