"Tensor Completion via Nonlocal Low-Rank Regularization"介绍了一种基于非局部低秩正则化的张量补全方法。该方法通过利用张量中的非局部结构信息,结合低秩正则化技术,实现了高效的张量补全。作者提出的方法在处理具有缺失值的张量数据时表现出良好的效果,并在实验中取得了较好的结果。该研究对于解决张量数据的缺失值...
which may result in an inability to recover the details of human motion with complex and diverse structures.Therefore, we propose a novel nonlocal low-rank regularization(NLR) method to model the structured sparsity according to the similarity of human motion, and we explore its application in hu...
Nonlocal low-rank regularizationTotal variationWeighted schatten-p normRecently, a nonlocal low-rank regularization based compressive sensing approach (NLR) which exploits structured sparsity of similar patches has shown the state-of-the-art performance in image......
In this paper, a nonlocal low-rank regularized CANDECOMP/PARAFAC (CP) tensor decomposition (NLR-CPTD) is proposed to fully utilize these two intrinsic priors. To make the rank estimation more accurate, a new manner of rank determination for the NLR-CPTD model is proposed. The i...
The local regularization term consists of two complementary parts - one characterizing the color-depth dependency in the gradient domain and the other in the spatial domain; nonlocal regularization involves a low-rank constraint suitable for large-scale depth discontinuities. Extensive experimental results...
Using the exponential regularization to the distributional integrals above, the result of the first integral is −π/2 and the other one, a δ-function, from which we obtain χq(r)∼r→∞−βκM2πr3, (110) for any classical higher-derivative model defined by analytic form factors....
Compressive sensing via nonlocal low-rank tensor regularization The aim of Compressing sensing (CS) is to acquire an original signal, when it is sampled at a lower rate than Nyquist rate previously. In the framework of ... L Feng,H Sun,Q Sun,... - 《Neurocomputing》 被引量: 97发表:...
Xin, "Nonlocal image restoration with bilateral variance estimation: A low-rank approach," IEEE Trans. Image Process., vol. 22, no. 2, pp. 700-711... Weisheng,Dong,Guangming,... - 《IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society》 被引量: 309...
Low-Rank RegularizationSalt-and-Pepper NoiseImage denoising has been a fundamental problem in the field of image processing. In this paper, we tackle removing impulse noise by combining the fractal image coding and the nonlocal self-similarity priors to recover image. The model undergoes a two-...
Fractal CodingImage DenoisingLow-Rank RegularizationFractal coding has been widely used as an image compression technique in many image processing problems in the past few decades. On the other hand side, most of the natural images have the characteristic of nonlocal self-similarity that motivates ...