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Paper Detail

Paper IDTEC-6.4
Paper Title A DISCRETE SCHEME FOR COMPUTING IMAGE’S WEIGHTED GAUSSIAN CURVATURE
Authors Yuanhao Gong, Wenming Tang, Lebin Zhou, Shenzhen University, China; Lantao Yu, Rice University, United States; Guoping Qiu, Shenzhen University, China
SessionTEC-6: Image and Video Processing 2
LocationArea G
Session Time:Monday, 20 September, 15:30 - 17:00
Presentation Time:Monday, 20 September, 15:30 - 17:00
Presentation Poster
Topic Image and Video Processing: Partial differential equation based processing of images & video
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Weighted Gaussian curvature is an important smoothness measurement for images. However, its conventional computation scheme has low performance, low accuracy and requires that the input image must be second order differentiable. To tackle these three issues, we propose a novel discrete computation scheme for the weighted Gaussian curvature. Our scheme does not require the second order differentiability. Moreover, our scheme is more accurate, has smaller support region and computationally more efficient than the conventional schemes. Therefore, our scheme holds promise for a large range of applications where the weighted Gaussian curvature is needed, for example, image smoothing, cartoon texture decomposition, optical flow estimation, etc.