WP1.L409.4
RETINEX-BASED IMAGE DENOISING / CONTRAST ENHANCEMENT USING GRADIENT GRAPH LAPLACIAN REGULARIZER
Yeganeh Gharedaghi, Gene Cheung, York University, Canada; Xianming Liu, Harbin Institute of Technology, China
Session:
WP1.L409: Graph Signal Processing and Machine Learning for Interpretable and robust image processing I Lecture
Track:
Special Sessions
Location:
Room 409
Presentation Time:
Wed, 11 Oct, 15:24 - 15:42 Malaysia Time (UTC +8)
Session Chair:
Yuichi Tanaka, Osaka University
Session WP1.L409
WP1.L409.1: Robust graph neural diffusion for image matching
Rui She, Qiyu Kang, Sijie Wang, Kai Zhao, Yang Song, Yi Xu, Tianyu Geng, Wee Peng Tay, Nanyang Technological University, Singapore; Diego Navarro, Andreas Hartmannsgruber, Continental Automotive Singapore Pte. Ltd., Singapore
WP1.L409.2: COMPLEXITY REDUCTION OF GRAPH SIGNAL DENOISING BASED ON FAST GRAPH FOURIER TRANSFORM
Takayuki Sasaki, Yukihiro Bandoh, Masaki Kitahara, NTT Corporation, Japan
WP1.L409.3: IMAGE CODING VIA PERCEPTUALLY INSPIRED GRAPH LEARNING
Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega, University of Southern California, United States of America
WP1.L409.4: RETINEX-BASED IMAGE DENOISING / CONTRAST ENHANCEMENT USING GRADIENT GRAPH LAPLACIAN REGULARIZER
Yeganeh Gharedaghi, Gene Cheung, York University, Canada; Xianming Liu, Harbin Institute of Technology, China
WP1.L409.5: INDUCTIVE GRAPH NEURAL NETWORKS FOR MOVING OBJECT SEGMENTATION
Wieke Prummel, Laboratoire Mathématiques, Image et Applications (MIA), La Rochelle Université, France; Jhony H. Giraldo, LTCI, Télécom Paris, Institut Polytechnique de Paris, France; Anastasia Zakharova, Thierry Bouwmans, Laboratoire Mathématiques, Image et Applications (MIA), La Rochelle Université, France
Contacts