Quaternion-Based Bilinear Factor Matrix Norm Minimization for Color Image Inpainting

L1-norm minimization for quaternion signals

—The l 1-norm minimization problem plays an important role in the compressed sensing (CS) theory. We present in this letter an algorithm for solving the problem of l 1 Index Terms—L-norm minimization for quaternion signals by converting it to second-order cone programming. An application example of the proposed algorithm is also given for practical guidelines of perfect recovery of quaternion s...

Factor Matrix Nuclear Norm Minimization for Low-Rank Tensor Completion

Most existing low-n-rank minimization algorithms for tensor completion suffer from high computational cost due to involving multiple singular value decompositions (SVDs) at each iteration. To address this issue, we propose a novel factor matrix rank minimization method for tensor completion problems. Based on the CANDECOMP/PARAFAC (CP) decomposition, we first formulate a factor matrix rank mini...

Factor Matrix Trace Norm Minimization for Low-Rank Tensor Completion

Most existing low-n-rank minimization algorithms for tensor completion suffer from high computational cost due to involving multiple singular value decompositions (SVDs) at each iteration. To address this issue, we propose a novel factor matrix trace norm minimization method for tensor completion problems. Based on the CANDECOMP/PARAFAC (CP) decomposition, we first formulate a factor matrix ran...

Quaternion K-SVD for Color Image Denoising

Image Zooming for Indexed Color Images Based on Bilinear Interpolation

In this paper, a novel image zooming scheme for indexed color images is proposed. In the proposed scheme, the bilinear interpolation technique is employed to enlarge the original image. Then, the pixel grouping process is executed to classify the pixels in the enlarged image. From the experimental results, it is shown that the proposed scheme provides better image quality than the pixel copy te...