68 citations · 82 across the 11 of their papers we have counts for
6 papers · 1 filter
Inheriting Bayer's Legacy-Joint Remosaicing and Denoising for Quad Bayer Image Sensor
Haijin Zeng, Kai Feng, Jiezhang Cao +5
Pixel binning based Quad sensors have emerged as a promising solution to overcome the hardware limitations of compact cameras in low-light imaging. However, binning results in lowe…
Low-rank Meets Sparseness: An Integrated Spatial-Spectral Total Variation Approach to Hyperspectral Denoising
Haijin Zeng, Shaoguang Huang, Yongyong Chen +2
Spatial-Spectral Total Variation (SSTV) can quantify local smoothness of image structures, so it is widely used in hyperspectral image (HSI) processing tasks. Essentially, SSTV ass…
Multi-mode Core Tensor Factorization based Low-Rankness and Its Applications to Tensor Completion
Haijin Zeng
Low-rank tensor completion has been widely used in computer vision and machine learning. This paper develops a novel multi-modal core tensor factorization (MCTF) method combined wi…
Enhanced nonconvex low-rank approximation of tensor multi-modes for tensor completion
Haijin Zeng, Xiaozhen Xie, Jifeng Ning
Higher-order low-rank tensor arises in many data processing applications and has attracted great interests. Inspired by low-rank approximation theory, researchers have proposed a s…
Hyperspectral Image Restoration via Global Total Variation Regularized Local nonconvex Low-Rank matrix Approximation
Haijin Zeng, Xiaozhen Xie, Jifeng Ning
Several bandwise total variation (TV) regularized low-rank (LR)-based models have been proposed to remove mixed noise in hyperspectral images (HSIs). Conventionally, the rank of LR…
Tensor completion using enhanced multiple modes low-rank prior and total variation
Haijin Zeng, Xiaozhen Xie, Jifeng Ning
In this paper, we propose a novel model to recover a low-rank tensor by simultaneously performing double nuclear norm regularized low-rank matrix factorizations to the all-mode mat…