2 citations · 3 across the 5 of their papers we have counts for
5 papers
Low Rank Quaternion Matrix Completion Based on Quaternion QR Decomposition and Sparse Regularizer
Juan Han, Liqiao Yang, Kit Ian Kou +2
Matrix completion is one of the most challenging problems in computer vision. Recently, quaternion representations of color images have achieved competitive performance in many fie…
Quaternion Tensor Train Rank Minimization with Sparse Regularization in a Transformed Domain for Quaternion Tensor Completion
Jifei Miao, Kit Ian Kou, Liqiao Yang +1
The tensor train rank (TT-rank) has achieved promising results in tensor completion due to its ability to capture the global low-rankness of higher-order (>3) tensors. On the other…
Quaternion Optimized Model with Sparse Regularization for Color Image Recovery
Liqiao Yang, Yang Liu, Kit Ian Kou
This paper addresses the color image completion problem in accordance with low-rank quatenrion matrix optimization that is characterized by sparse regularization in a transformed d…
Low Rank Quaternion Matrix Recovery via Logarithmic Approximation
Liqiao Yang, Jifei Miao, Kit Ian Kou
In color image processing, image completion aims to restore missing entries from the incomplete observation image. Recently, great progress has been made in achieving completion by…
Weighted Truncated Nuclear Norm Regularization for Low-Rank Quaternion Matrix Completion
Liqiao Yang, Kit Ian Kou, Jifei Miao
In recent years, quaternion matrix completion (QMC) based on low-rank regularization has been gradually used in image de-noising and de-blurring.Unlike low-rank matrix completion (…