sis 22(36): e13

Research Article

A novel Gauss-Laplace operator based on multi-scale convolution for dance motion image enhancement

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  • @ARTICLE{10.4108/eai.17-12-2021.172439,
        author={Dianhuai Shen and Xueying Jiang and Lin Teng},
        title={A novel Gauss-Laplace operator based on multi-scale convolution for dance motion image enhancement},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={9},
        number={36},
        publisher={EAI},
        journal_a={SIS},
        year={2021},
        month={12},
        keywords={dance image enhancement, Gauss-Laplace operator, multi-scale convolution},
        doi={10.4108/eai.17-12-2021.172439}
    }
    
  • Dianhuai Shen
    Xueying Jiang
    Lin Teng
    Year: 2021
    A novel Gauss-Laplace operator based on multi-scale convolution for dance motion image enhancement
    SIS
    EAI
    DOI: 10.4108/eai.17-12-2021.172439
Dianhuai Shen1, Xueying Jiang2, Lin Teng3,*
  • 1: College of Music and Dance, Huaqiao University, Xiamen 361000 Fujian, China
  • 2: School of Public Policy and Management, Tsinghua University, Beijing 100000 China
  • 3: Software College, Shenyang Normal University, Shenyang 110034 China
*Contact email: 910675024@qq.com

Abstract

This article has been retracted, and the retraction notice can be found here: http://dx.doi.org/10.4108/eai.8-4-2022.173797. Traditional image enhancement methods have the problems of low contrast and fuzzy details. Therefore, we propose a novel Gauss-Laplace operator based on multi-scale convolution for dance motion image enhancement. Firstly, multi-scale convolution is used to preprocess the image. Then, we improve the traditional Laplace edge detection operator and combine it with Gauss filter. The Gaussian filter is used to smooth the image and suppress the noise, and the edge detection is processed based on the Laplace gradient edge detector. The detail image extracted by Gauss-Laplace operator and the image with brightness enhancement are linearly weighted fused to reconstruct the image with clear detail edge and strong contrast. Experiments are carried out with detailed images in different scenes. It is compared with traditional methods to verify the effectiveness of the proposed method.