Technical Program: Paper Detail || IEEE IGARSS 2023 || Pasadena, California, USA || 16

FRP.P7.6

NEW INFORMED LINEAR MIXING MODEL AND NMF-BASED UNMIXING METHOD ADDRESSING SPECTRAL VARIABILITY WITH AN APPLICATION TO MINERAL DETECTION AND MAPPING USING PRISMA HYPERSPECTRAL REMOTE SENSING DATA

Fatima Zohra Benhalouche, Oussama Benabbou, Oualid Yahia, Moussa Sofiane Karoui, Agence Spatiale Algérienne, Algeria; Yannick Deville, Université de Toulouse, France; Lahsen Wahib Kebir, Ahmed Bennia, Agence Spatiale Algérienne, Algeria

Session:

FRP.P7: Hyperspectral Unmixing Poster

Location:

Poster Area 7

Presentation Time:

Fri, 21 Jul, 14:15 - 15:45 Pacific Time (UTC -8)

Session Chair:

Miguel Velez-Reyes, The University of Texas at El Paso

Session Managers:

Srashti Singh and NIMA ESMAEILZADEH and Suhaimee Buya and sunni kanta prasad kushwaha

Session FRP.P7

FRP.P7.1: A SPECTRAL–SPATIAL ATTENTION AUTOENCODER NETWORK FOR HYPERSPECTRAL UNMIXING

Jie Wang, Jindong Xu, Yantai University, China

FRP.P7.2: COLLABORATIVE CONSISTENCY AUTOENCODER HYPERSPECTRAL UNMIXING USING DEEP IMAGE PRIOR

Min Huang, Nanchang Institute of Technology, China; Mengxiong Tang, GMC Building, China; Fan Li, Shaoquan Zhang, Shengqian Wang, Ningyuan Zhang, Chengzhi Deng, Nanchang Institute of Technology, China

FRP.P7.3: AN ITERATIVE METHOD FOR HYPERSPECTRAL PIXEL UNMIXING LEVERAGING LATENT DIRICHLET VARIATIONAL AUTOENCODER

Kiran Mantripragada, Ontario Tech University, Canada; Paul R. Adler, United States Department of Agriculture, Canada; Peder A. Olsen, Microsoft Research, Canada; Faisal Z. Qureshi, Ontario Tech University, Canada

FRP.P7.4: A DUAL-STREAM CONVOLUTIONAL FEATURE FUSION NETWORK FOR HYPERSPECTRAL UNMIXING

Haoyue Hua, Jie Li, Ying Wang, Xinbo Gao, Xidian University, China

FRP.P7.5: A NOVEL LINEAR MIXING MODEL ADDRESSING SPECTRAL-SPATIAL INTRA-CLASS VARIABILITY WITH AN ASSOCIATED PENALIZED NMF-BASED HYPERSPECTRAL UNMIXING ALGORITHM

Moussa Sofiane Karoui, Fatima Zohra Benhalouche, Agence Spatiale Algérienne, Algeria; Yannick Deville, Université de Toulouse, France

FRP.P7.6: NEW INFORMED LINEAR MIXING MODEL AND NMF-BASED UNMIXING METHOD ADDRESSING SPECTRAL VARIABILITY WITH AN APPLICATION TO MINERAL DETECTION AND MAPPING USING PRISMA HYPERSPECTRAL REMOTE SENSING DATA

FRP.P7.7: UNMIXING ANALYSIS OF CLOSE-RANGE HYPERSPECTRAL IMAGES

Ana Chavez-Lopez, Miguel Velez-Reyes, The University of Texas at El Paso, United States

FRP.P7.8: A SHUFFLED DILATED CONVOLUTIONAL NEURAL NETWORK FOR HYPERSPECTRAL IMAGE USING TRANSFER LEARNING

Koushikey Chhapariya, Krishna Mohan Buddhiraju, IIT Bombay, India; Anil Kumar, IIRS, ISRO, India

FRP.P7.9: WAVELET TRANSFORM BASED NETWORK FOR SPECTRAL SUPER-RESOLUTION

Weixin Ren, Qianyue Duan, Tiange Huang, Lei Zhang, Wei Wei, Northwestern Polytechnical University, China; Chen Ding, Xi’an University of Posts and Telecommunications, China; Yanning Zhang, Northwestern Polytechnical University, China

FRP.P7.10: PIXEL- AND PATCH-WISE CONTEXT-AWARE LEARNING WITH CNN AND GCN COLLABORATION FOR HYPERSPECTRAL IMAGE CLASSIFICATION

Hong Wang, Kun Gao, Xiaodian Zhang, Junwei Wang, Zibo Hu, Zhijia Yang, Beijing Institute of technology, China; Yuxuan Mao, Beijing Institute of Technology, China; Yutong Liu, Beijing Institute of technology, China

FRP.P7.11: GL-NET:GAUSSIAN LEADING NETWORK FOR SAR SHIP DETECTION

Zenghao Chen, Yanan You, Wenli Zhou, Meng Gang, Beijing University of Posts and Telecommunications, China

FRP.P7.12: HYBRID TRANSFORMER NETWORK FOR CHANGE DETECTION UNDER SELF-SUPERVISED PRETRAINING

Yongjing Cui, Yin Zhuang, Shan Dong, Xinyi Zhang, Beijing Key Laboratory of Embedded Real-time Information Processing Technology, Beijing Institute of Technology, China; Peng Gao, Shanghai AI Laboratory, China; He Chen, Liang Chen, Beijing Key Laboratory of Embedded Real-time Information Processing Technology, Beijing Institute of Technology, China