• The Journal of the Acoustical Society of Korea
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• v.31 no.8
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• pp.532-541
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• 2012

An underwater transient signal is distinguished from an ambient noise. Database for the underwater transient signal is required since the underwater transient signal shows various characteristics depending on acoustic features. In the paper, hence, sound mask-filter was applied to extract the transient signals which exist temporally and locally in the ocean. The standard signal was chosen and cross-correlated with the raw signal. A mask-filter for a transient signal was obtained using the threshold which was decided by the maximum likelihood method in the envelope of the cross-correlated signal. Using the sound mask-filter, the transient signal of a sea catfish {Galeichthys felis (Linnaeus)} was extracted from the underwater ambient noise. Similarly, the man-made signal was added into the noise and it was extracted by the same method. We also have demonstrated the significance of the transient signal through comparing the extracted signals depending on the standard signal. In the results, the proposed method, sound mask-filtering, could be utilized as a database construction of the transient signals in underwater noise. Particularly, this study would be useful to extract the wanted signal from arbitrary signals.

• Journal of the Korean Society of Radiology
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• v.17 no.1
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• pp.157-165
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• 2023

Ultrasound imaging uses sound waves of frequencies to cause physical actions such as reflection, absorption, refraction, and transmission at the edge between different tissues. Improvement is needed because there is a lot of noise due to the characteristics of the data generated from the ultrasound equipment, and it is difficult to grasp the shape of the tissue to be actually observed because the edge is vague. The edge enhancement method is used as a method to solve the case where the edge surface looks clumped due to a decrease in image quality. In this paper, as a method to strengthen the interface, the quality improvement was confirmed by strengthening the interface, which is the high-frequency part, in each image using an unsharpening mask and high boost. The mask filtering used for each image was evaluated by measuring PSNR and SNR. Abdominal, head, heart, liver, kidney, breast, and fetal images were obtained from Philips epiq5g and affiniti70g and Alpinion E-cube 15 ultrasound equipment. The program used to implement the algorithm was implemented with MATLAB R2022a of MathWorks. The unsharpening and high-boost mask array size was set to 3*3, and the laplacian filter, a spatial filter used to create outline-enhanced images, was applied equally to both masks. ImageJ program was used for quantitative evaluation of image quality. As a result of applying the mask filter to various ultrasound images, the subjective image quality showed that the overall contour lines of the image were clearly visible when unsharpening and high-boost mask were applied to the original image. When comparing the quantitative image quality, the image quality of the image to which the unsharpening mask and the high boost mask were applied was evaluated higher than that of the original image. In the portal vein, head, gallbladder, and kidney images, the SNR, PSNR, RMSE and MAE of the image to which the high-boost mask was applied were measured to be high. Conversely, for images of the heart, breast, and fetus, SNR, PSNR, RMSE and MAE values were measured as images with the unsharpening mask applied. It is thought that using the optimal mask according to the image will help to improve the image quality, and the contour information was provided to improve the image quality.