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Abstract. The Mumford-Shah model is one of the most important image segmentation models, and has been studied extensively in the last twenty years. In this paper, we propose a two-stage segmentation method based on the Mumford-Shah model. The first stage of our method is to find a smooth solution g to a convex variant of the Mumford-Shah model. Once g is(More)
Framelets have been used successfully in various problems in image processing, including inpainting, impulse noise removal, superresolution image restoration, etc. Segmentation is the process of identifying object outlines within images. There are quite a few efficient algorithms for segmentation that depend on the partial differential equation modeling. In(More)
This paper addresses the problems of disparity and optical flow partitioning based on the brightness invariance assumption. We investigate new variational approaches to these problems with Potts priors and possibly box constraints. For the optical flow partitioning, our model includes vector-valued data and an adapted Potts regularizer. Using the notion of(More)
Tight-frame, a generalization of orthogonal wavelets, has been used successfully in various problems in image processing, including inpainting, impulse noise removal, super-resolution image restoration, etc. Segmentation is the process of identifying object outlines within images. There are quite a few efficient algorithms for segmentation such as the model(More)
Image segmentation and image restoration are two important topics in image processing with great achievements. In this paper, we propose a new multiphase segmentation model by combining image restoration and image segmentation models. Utilizing image restoration aspects, the proposed segmentation model can effectively and robustly tackle high noisy images,(More)
There is much current interest in using multisensor airborne remote sensing to monitor the structure and biodiversity of woodlands. This paper addresses the application of nonparametric (NP) image-registration techniques to precisely align images obtained from multisensor imaging, which is critical for the successful identification of individual trees using(More)
Segmentation is the process of identifying object outlines within images. There are a number of efficient algorithms for segmentation in Euclidean space that depend on the variational approach and partial differential equation modelling. Wavelets have been used successfully in various problems in image processing, including segmentation, inpainting, noise(More)
Denoising of the ECG signals is required, as they are prone to noises during their acquisition. Currently, denoising techniques for ECG signals are mostly available in the wavelet transform domain. In this paper, an approach for denoising the ECG signals in the Framelet domain is proposed. Initially, signals are decomposed using the Framelet transform.(More)