Blended noise suppression using a hybrid median filter, normal moveout and complex curvelet transform approach

Dong, Li; Wang, Changhui; Zhang, Mugang; Wang, Deying; Liang, Xifeng

doi:10.1007/s11200-020-0269-9

Cited by 3 publications

(2 citation statements)

References 22 publications

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“…e image captured by the camera is easily disturbed and polluted by noise in the process of transmission, conversion, and storage, which will make the useful information in the image unable to be extracted. erefore, after capturing and converting the image, this paper uses the median filter [26,27] to suppress the noise in the image. In order to perform median filtering on a pixel point on an image, the pixel values of the desired pixel in the mask and its neighborhood must be sorted to determine the median, and the median is given to the pixel point, which is expressed as follows:…”

Section: Image Capture and Preprocessingmentioning

confidence: 99%

Concrete Application of Computer Virtual Image Technology in Modern Sports Training

Chi

Li²

2022

Computational Intelligence and Neuroscience

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The efficiency of basketball shooting training has always been an urgent problem to be solved in basketball sports. Applying computer virtual image technology to basketball sports training is the key to improve basketball shooting ability and improve the effect of basketball sports training. Therefore, based on the design of basketball shooting automatic recognition system based on the background difference method, this study puts forward the specific application of computer virtual image technology in modern sports training. By analyzing the techniques of image denoising, image detection, and image calibration, a goal detection algorithm for modern sports basketball shooting training is designed. Firstly, the camera is used for image capture, the RGB image is converted into gray image, and the median filter is used to suppress the noise in the image. Then, the background difference method is used to detect the moving region, and the background modeling is combined with the mean method. After obtaining the background reference model, the image is differentiated, the gray image after image difference is binarized, and then the binary image is postprocessed by morphological middle closure operation. Finally, the image calibration technology is used to extract the basketball feature information. Through the region segmentation algorithm, the basketball shooting part is segmented and judged, so as to realize the basketball shooting training goal detection. The experimental results show that the proposed method has a good effect on basketball shooting training goal detection and can effectively improve the detection accuracy and efficiency.

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Section: Image Capture and Preprocessingmentioning

confidence: 99%

Concrete Application of Computer Virtual Image Technology in Modern Sports Training

Chi

Li²

2022

Computational Intelligence and Neuroscience

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“…A blended sound is a mixture or combination of different sounds occurring simultaneously, resulting in a complex auditory experience [14].…”

Section: Introductionmentioning

confidence: 99%

Experimental study of sound wave propagation patterns

Imanov,

Kozhas,

Mukhamejanova

et al. 2024

tbus

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The present study compares the behavior of different sound types and their sources concerning distance. Experimental findings demonstrate a consistent reduction in noise levels with increasing distance from the sound origin, aligning with anticipated sound propagation patterns. Median noise level reductions are quantified, showing decreases from 72.7 dB at the source to 54.8 dB at a distance. Pulsed sounds exhibit pronounced fluctuations and peaks at close distances, while steady and blended sounds maintain more uniform levels. An exponential model accurately characterizes the noise reduction phenomenon (R² = 0.8664), underscoring its relevance for noise management, urban planning, and acoustic engineering applications. These results offer valuable insights into sound propagation dynamics and provide a basis for developing effective noise control strategies and optimizing environmental acoustics.

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Self-similarity convolution neural network for seismic noise suppression in desert environment

Lin,

Xu,

Wang

2023

Stud Geophys Geod

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Blended noise suppression using a hybrid median filter, normal moveout and complex curvelet transform approach

Cited by 3 publications

References 22 publications

Concrete Application of Computer Virtual Image Technology in Modern Sports Training

Concrete Application of Computer Virtual Image Technology in Modern Sports Training

Experimental study of sound wave propagation patterns

Self-similarity convolution neural network for seismic noise suppression in desert environment

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