Category: IEEE 2017

Image Segmentation Using Parametric Contours With Free Endpoints

Image Segmentation Using Parametric Contours With Free Endpoints Abstract: In this paper, we introduce a novel approach for active contours with free endpoints. A scheme for image segmentation is presented based on a discrete version of the Mumford-Shah functional where the contours can be both closed and open curves. Additional to a flow of the […]


Learning Iteration-wise Generalized Shrinkage-Thresholding Operators for Blind Deconvolution

Learning  Iteration-wise  Generalized  Shrinkage-Thresholding  Operators  for Blind Deconvolution Abstract: Salient edge selection and time-varying regularization are two crucial techniques to guarantee the success of maximum a posteriori (MAP)-based blind deconvolution. However, the existing approaches usually rely on carefully designed regularizers and handcrafted parameter tuning to obtain satisfactory estimation of the blur kernel. Many regularizers exhibit […]