Jinming Duan

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A second order Mumford-Shah model is proposed for image denoising. Unlike the original Mumford-Shah model, the proposed new model uses second order derivatives defined in bounded Hessian space as its regulariser. This model is capable of eliminating the undesirable staircase effect associated with the original Mumford-Shah model with a total variation(More)
The classical TV (Total Variation) model has been applied to gray texture image denoising and inpainting previously based on the non local operators, but such model can not be directly used to color texture image inpainting due to coupling of different image layers in color images. In order to solve the inpainting problem for color texture images(More)
—In this paper, we present a novel variational framework for multiphase synthetic aperture radar (SAR) image segmentation based on the fuzzy region competition method. A new energy functional is proposed to integrate the Gamma model and the edge detector based on the ratio of exponentially weighted averages (ROEWA) operator within the optimization process.(More)
Optical coherence tomography (OCT) imaging plays an important role in clinical diagnosis and monitoring of diseases of the human retina. Automated analysis of optical coherence tomography images is a challenging task as the images are inherently noisy. In this paper, a novel variational image decomposition model is proposed to decompose an OCT image into(More)