RETRACTED: A novel Gauss-Laplace operator based on multi-scale convolution for dance motion image enhancement [EAI Endorsed Scal Inf Syst (2022), Online First]

Abstract

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.

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“…The Gaussian Laplace operator extracts the gradient of the image in the horizontal and vertical directions, but it is weak for extracting the gradient of the image in the positive and reverse 45-degree directions, which results in the phenomenon that the edges are not completely wrapped [29] . Therefore, the gradients of the image in the positive and reverse 45-degree directions are extracted and merged with the image extracted by the Gaussian Laplacian operator to realize the complete extraction of the edges.…”