Nonlocal data fidelity termIn this paper, we propose an improved model for image decomposition and denoising based on Shearlet and nonlocal data fidelity term. The model splits an image into three parts: the cartoon component modeled by total variation (TV) space, the texture component modeled ...
The data distribution is [*,*,Block], where “Block” distribution assigns a contiguous block of array elements to each processor and “*” means no distribution in that dimension. In the computation of the finite volume scheme, each processor will be responsible for calculations in the sub...
(41) can be proven to hold for any set of distinct numbers {mi2} [36], it is not necessary to work with the expression of the coefficients Cj in terms of mi to verify the cancellation of the singularity, since (40) is merely a consequence of the partial fraction decomposition, as ...
aArchitecture overview, for details on the nuclear and electronic (charge/spin) embeddings and basis functions, refer to Eqs. (9), (10), and (13), respectively.bInteraction module, see Eq. (11).cLocal interaction block, see Eq. (12).dNonlocal interaction block, see Eq. (18).eResidua...
First, it employs the singular value decomposition (SVD) method and the K-means clustering (K-means) technique for robust classification of blocks in noisy images. Second, the local window is adaptively adjusted to match the local property of a block. Finally, a rotated block matching ...
The proposed method employs the singular value decomposition (SVD) method and the K-means clustering (K-means) technique to achieve robust block classification in noisy images. Then, a local window is adaptively adjusted to match the local property of a block. Finally, a rotated block matching...
We define the regularization term as a weighted sum of two terms, where the first term is the ordinary nonlocal TV based on the first-order and the second term is based on the second-order. Additionally, in this paper, we introduce a newly discovered idea called nonlocal Total K-Split ...
In order to solve the problems of long-term image acquisition time and massive data processing in a terahertz time domain spectroscopy imaging system, a novel fast terahertz imaging model, combined with group sparsity and nonlocal self-similarity (GSNS), is proposed in this paper. In GSNS, th...
then proposed the block-matching and 3D filtering (BM3D) method [12], which takes advantage of both the space and frequency domains. It firstly groups similar 2D image blocks into 3D data arrays, and secondly performs the 3D wavelet transform on the obtained 3D data arrays, thirdly applies ...
Each band of HSI is a gray image, and it can be denoised band-wise by traditional gray-level image denoising methods, such as the nonlocal-based algorithm [19], K-singular value decomposition (K-SVD) [20], and block-matching 3-D filtering (BM3D) [21]. The band-wise methods ignore...