# Improvement of [PERSON]'s Stripe Noise Suppression Method for Side-Scan Sonar Images
###### Abstract  
In response to the problem of stripe noise significantly reducing the clarity and details of side-scan sonar images due to various factors, the authors of this paper propose an improved Criminisi method for stripe noise suppression. To address the issues encountered in the Criminisi algorithm during the suppression of stripe noise in side-scan sonar images, the following steps are suggested: firstly, introduce dynamic weights in the priority calculation to adaptively adjust the confidence and data term weights based on the current patch's texture complexity; secondly, utilize the Sobel operator in the data term calculation to capture the image edge information more accurately, and, thirdly, optimize the matching block search process by introducing the Manhattan distance in addition to the Sum of Squared Differences (SSD) criterion to further select the best matching block while transitioning from a global search to a local search. Experimental validation was conducted using simulated stripe noise images, comparing the proposed method with four traditional denoising techniques. The results demonstrate that the denoising effectiveness of the proposed method is superior, effectively restoring texture in noisy regions while preserving texture structure integrity. Ablation experiments validate the effectiveness of the proposed improvements. Denoising experiments on real noisy images show satisfactory results with this method, and combining it with Fourier transform for additional smoothing in certain cases may yield even better results. s +
Footnote †: journal: Applied sciences  
article  
**Clication:** [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON], [PERSON]; [PERSON], [PERSON]; [PERSON], [PERSON] Improvement of Criminisi's Stripe Noise Suppression Method for Side-Scan Sonar Images. _Appl. Sci._**2024**, 14, 9574. [[https://doi.org/10.3390/app14209574](https://doi.org/10.3390/app14209574)]([https://doi.org/10.3390/app14209574](https://doi.org/10.3390/app14209574))  
**Classification:** [PERSON]; [PERSON], [PERSON]; [PERSON], [PERSON]; [PERSON], [PERSON]; [PERSON], [PERSON]; [PERSON], [PERSON]; [PERSON], [PERSON] Improvement of Criminisi's Stripe Noise Suppression Method for Side-Scan Sonar Images. _Appl. Sci._**2024**, 14, 9574. [[https://doi.org/10.3390/app14209574](https://doi.org/10.3390/app14209574)]([https://doi.org/10.3390/app14209574](https://doi.org/10.3390/app14209574))  
**Classification:** [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON], [PERSON]; [PERSON], [PERSON], C. Improvement of Criminisi's Stripe Noise Suppression Method for Side-Scan Sonar Images. _Appl. Sci._**2024**, 14, 9574. [[https://doi.org/10.3390/app14209574](https://doi.org/10.3390/app14209574)]([https://doi.org/10.3390/app14209574](https://doi.org/10.3390/app14209574))
Currently, most methods for noise suppression in side-scan sonar images employ spatial domain processing techniques similar to those used in optical images, such as median filtering [10] and wavelet decomposition [11; 12], primarily addressing speckle noise and salt-and-pepper noise, with minimal effect on stripe noise. For instance, [PERSON] et al. proposed using wavelet decomposition to filter out stripe noise [11], achieving some effectiveness but sacrificing image clarity. [PERSON] et al. introduced one-dimensional guided filtering (1D-GF) for stripe noise removal [13], achieving a good balance between removing stripe noise and preserving details but causing some blurring along horizontal and vertical edges. [PERSON] and [PERSON], respectively, utilized two-dimensional Fourier transforms to eliminate stripe noise [14; 15]; although achieving some effectiveness, the denoised images often exhibited shadowing of a certain width. [PERSON] et al. [16] proposed a denoising method that combines two-dimensional empirical module decomposition and the non-local mean algorithm; this method aims to suppress speckle noise and multiplicative specular noise in side-scan sonar images, but it is not suitable for fringe noise.