Abstract
In order to suppress the multiplicative specular noise in side-scan sonar images, a denoising method combining bidimensional empirical mode decomposition and non-local means algorithm is proposed. First, the sonar image is decomposed into intrinsic mode functions(IMF) and residual component, then the high frequency IMF is denoised by non-local mean filtering method, and finally the processed intrinsic mode functions and residual component are reconstructed to obtain the de-noised side-scan sonar image. The paper’s method is compared with the conventional filtering algorithm for experimental quantitative analysis. The results show that this method can suppress the sonar image noise and retain the detailed information of the image, which is beneficial to the later image processing.
Highlights
With the development and utilization of marine resources and the in-depth exploration of the ocean, seabed topographic survey and ocean target detection have become hot issues
It can be seen from the image and screening process that the first two intrinsic mode functions (IMF) components obtained after decomposition contain the high-order frequency components of the original image signal
Step 3 The processed high-frequency IMFh (x, y), low-frequency IMFl (x, y) and the residual component R(x, y) were reconstructed to obtain the noise reduction image processed by BEMD-IMF : N (x=, y) NIMFh (x, y) IMFl (x, y) R(x, y) (10) The high-frequency IMF contains the main information and noise of the original image, while the residual component still retains part of the image details, so the residual component should be retained in the final image reconstruction
Summary
With the development and utilization of marine resources and the in-depth exploration of the ocean, seabed topographic survey and ocean target detection have become hot issues. Sonar image is an important achievement of side-scan sonar work and a manifestation of ocean information. Side-scan sonar image denoising is a pre-processing work, which is of great significance for obtaining image information and provides guarantee for subsequent image segmentation, mosaic and target recognition. For noise suppression of side-scan sonar images, optical images' spatial domain noise removal algorithms, such as median filtering and mean filtering, are mostly used at present[3]. These methods are not very skilled in suppressing speckle noise in side-scan sonar images. The denoising effect of this method is obvious, and the details and edge information of the image are effectively retained
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