activity
20172020
most citedRestricted Structural Random Matrix for Compressive Sensing

1 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

eess.IV20201 cited

Multi-Scale Deep Compressive Imaging

Thuong Nguyen Canh, Byeungwoo Jeon

Recently, deep learning-based compressive imaging (DCI) has surpassed the conventional compressive imaging in reconstruction quality and faster running time. While multi-scale has…

eess.SP20201 cited

Restricted Structural Random Matrix for Compressive Sensing

Thuong Nguyen Canh, Byeungwoo Jeon

Compressive sensing (CS) is well-known for its unique functionalities of sensing, compressing, and security (i.e. CS measurements are equally important). However, there is a tradeo…

cs.CV2018

Multi-Scale Deep Compressive Sensing Network

Thuong Nguyen Canh, Byeungwoo Jeon

With joint learning of sampling and recovery, the deep learning-based compressive sensing (DCS) has shown significant improvement in performance and running time reduction. Its rec…

eess.IV2017

Compressive Sensing of Color Images Using Nonlocal Higher Order Dictionary

Khanh Quoc Dinh, Thuong Nguyen Canh, Byeungwoo Jeon

This paper addresses an ill-posed problem of recovering a color image from its compressively sensed measurement data. Differently from the typical 1D vector-based approach of the s…

cs.CV2017

Block Compressive Sensing of Image and Video with Nonlocal Lagrangian Multiplier and Patch-based Sparse Representation

Trinh Van Chien, Khanh Quoc Dinh, Byeungwoo Jeon +1

Although block compressive sensing (BCS) makes it tractable to sense large-sized images and video, its recovery performance has yet to be significantly improved because its recover…