100 citations · 116 across the 14 of their papers we have counts for
8 papers · 1 filter
A New Cross-Space Total Variation Regularization Model for Color Image Restoration with Quaternion Blur Operator
Zhigang Jia, Yuelian Xiang, Meixiang Zhao +2
The cross-channel deblurring problem in color image processing is difficult to solve due to the complex coupling and structural blurring of color pixels. Until now, there are few e…
A New Low-Rank Learning Robust Quaternion Tensor Completion Method for Color Video Inpainting Problem and Fast Algorithms
Zhigang Jia, Jingfei Zhu
The color video inpainting problem is one of the most challenging problem in the modern imaging science. It aims to recover a color video from a small part of pixels that may conta…
Quasi Non-Negative Quaternion Matrix Factorization with Application to Color Face Recognition
Yifen Ke, Changfeng Ma, Zhigang Jia +2
To address the non-negativity dropout problem of quaternion models, a novel quasi non-negative quaternion matrix factorization (QNQMF) model is presented for color image processing…
Non-Local Robust Quaternion Matrix Completion for Color Images and Videos Inpainting
Zhigang Jia, Qiyu Jin, Michael K. Ng +1
The image nonlocal self-similarity (NSS) prior refers to the fact that a local patch often has many nonlocal similar patches to it across the image and has been widely applied in m…
Generalized Two-Dimensional Quaternion Principal Component Analysis with Weighting for Color Image Recognition
Zhi-Gang Jia, Zi-Jin Qiu, Qian-Yu Wang +2
One of the most powerful methods of color image recognition is the two-dimensional principle component analysis (2DQPCA) approach, which is based on quaternion representation and p…
Advanced Variations of Two-Dimensional Principal Component Analysis for Face Recognition
Meixiang Zhao, Zhigang Jia, Yunfeng Cai +2
The two-dimensional principal component analysis (2DPCA) has become one of the most powerful tools of artificial intelligent algorithms. In this paper, we review 2DPCA and its vari…
Relaxed 2-D Principal Component Analysis by Norm for Face Recognition
Xiao Chen, Zhi-Gang Jia, Yunfeng Cai +1
A relaxed two dimensional principal component analysis (R2DPCA) approach is proposed for face recognition. Different to the 2DPCA, 2DPCA- and G2DPCA, the R2DPCA utilizes the l…
Sample-Relaxed Two-Dimensional Color Principal Component Analysis for Face Recognition and Image Reconstruction
Meixiang Zhao, Zhigang Jia, Dunwei Gong
A sample-relaxed two-dimensional color principal component analysis (SR-2DCPCA) approach is presented for face recognition and image reconstruction based on quaternion models. A re…