4.7 Article

Adversarial Spectral Super-Resolution for Multispectral Imagery Using Spatial Spectral Feature Attention Module

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Computer Science, Artificial Intelligence

Deep Hybrid 2-D-3-D CNN Based on Dual Second-Order Attention With Camera Spectral Sensitivity Prior for Spectral Super-Resolution

Jiaojiao Li et al.

Summary: A largely ignored fact in spectral super-resolution (SSR) is that the subsistent mapping methods neglect the auxiliary prior of camera spectral sensitivity (CSS) and only pay attention to wider or deeper network framework design while ignoring to excavate the spatial and spectral dependencies among intermediate layers, hence constraining representational capability of convolutional neural networks (CNNs). To conquer these drawbacks, we propose a novel deep hybrid 2-D-3-D CNN based on dual second-order attention with CSS prior (HSACS), which can excavate sufficient spatial-spectral context information. The experimental results demonstrate the superiority and progressiveness of the presented approach in terms of quantitative metrics and visual effect over SOTA SSR methods.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2023)

Article Geochemistry & Geophysics

HASIC-Net: Hybrid Attentional Convolutional Neural Network With Structure Information Consistency for Spectral Super-Resolution of RGB Images

Jiaojiao Li et al.

Summary: Spectral super-resolution is a technique for recovering a reasonable hyperspectral image from a single RGB image, and it has been widely used in remote sensing image processing. Existing algorithms suffer from poor channel or band feature extraction and fusing performance, but a novel hybrid attentional CNN with structure information consistency (HASIC-net) has been proposed to address these issues and achieve better performance.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2022)

Article Geochemistry & Geophysics

Spectral Super-Resolution of Multispectral Images Using Spatial-Spectral Residual Attention Network

Xiangtao Zheng et al.

Summary: This study introduces a novel network architecture that can simultaneously explore the spatial and spectral information of multispectral images, leading to the reconstruction of hyperspectral images.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2022)

Article Geochemistry & Geophysics

Spectral Superresolution of Multispectral Imagery With Joint Sparse and Low-Rank Learning

Lianru Gao et al.

Summary: Extensive attention has been paid to enhancing the spatial resolution of hyperspectral images using multispectral images in remote sensing. This study introduces a novel approach to improve the spectral resolution of remote sensing imagery by super-resolving multispectral images in the spectral domain. The developed joint sparse and low-rank learning (J-SLoL) method effectively enhances multispectral images by learning low-rank HS-MS dictionary pairs from overlapped regions, showing superior performance compared to existing state-of-the-art baselines.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2021)

Article Computer Science, Artificial Intelligence

Spectral Super-Resolution Network Guided by Intrinsic Properties of Hyperspectral Imagery

Renlong Hang et al.

Summary: This study designed a spectral super-resolution network based on the spectral correlation and projection property of hyperspectral imagery. By utilizing a decomposition subnetwork and a self-supervised subnetwork, the end-to-end super-resolution network achieved competitive reconstruction performance compared to state-of-the-art networks on widely used HSI datasets.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2021)

Article Engineering, Electrical & Electronic

Adaptive Nonnegative Sparse Representation for Hyperspectral Image Super-Resolution

Xuesong Li et al.

Summary: This article proposes an adaptive nonnegative sparse representation-based model to fuse hyperspectral images (HSI) and their corresponding multispectral images (MSI) for enhancing the spatial resolution of HSIs. The method alternately optimizes the spectral basis and coefficients to balance sparsity and collaboration in order to achieve more accurate results. Experimental results demonstrate the superiority of this approach over other state-of-the-art HSI super-resolution methods.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2021)

Article Engineering, Electrical & Electronic

Bidirectional 3D Quasi-Recurrent Neural Network for Hyperspectral Image Super-Resolution

Ying Fu et al.

Summary: This article introduces a deep learning-based method for hyperspectral image (HSI) spatial super-resolution that addresses the lack of structural spatial-spectral correlation and global correlation along spectra in existing methods. By designing a bidirectional 3D quasi-recurrent neural network and combining domain knowledge of HSI with a novel pretraining strategy, the method achieves super-resolution on HSI with an arbitrary number of bands. Extensive evaluations and comparisons show improvements in restoration accuracy and visual quality over state-of-the-art methods for HSI super-resolution.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2021)

Article Computer Science, Artificial Intelligence

Hyperspectral Recovery from RGB Images using Gaussian Processes

Naveed Akhtar et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2020)

Article Geochemistry & Geophysics

Spatial and Spectral Joint Super-Resolution Using Convolutional Neural Network

Shaohui Mei et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2020)

Article Geochemistry & Geophysics

Spectral Super Resolution of Hyperspectral Images via Coupled Dictionary Learning

Konstantina Fotiadou et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2019)

Article Geochemistry & Geophysics

Spectral Super-Resolution for Multispectral Image Based on Spectral Improvement Strategy and Spatial Preservation Strategy

Chen Yi et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2019)

Article Computer Science, Information Systems

HRAN: Hybrid Residual Attention Network for Single Image Super-Resolution

Abdul Muqeet et al.

IEEE ACCESS (2019)

Proceedings Paper Computer Science, Artificial Intelligence

Deeply Learned Filter Response Functions for Hyperspectral Reconstruction

Shijie Nie et al.

2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (2018)

Proceedings Paper Computer Science, Artificial Intelligence

HSCNN plus : Advanced CNN-Based Hyperspectral Recovery from RGB Images

Zhan Shi et al.

PROCEEDINGS 2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW) (2018)

Proceedings Paper Computer Science, Artificial Intelligence

HSCNN: CNN-Based Hyperspectral Image Recovery from Spectrally Undersampled Projections

Zhiwei Xiong et al.

2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2017) (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Adversarial Networks for Spatial Context-Aware Spectral Image Reconstruction from RGB

Aitor Alvarez-Gila et al.

2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2017) (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Densely Connected Convolutional Networks

Gao Huang et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

Article Computer Science, Artificial Intelligence

Image Super-Resolution Using Deep Convolutional Networks

Chao Dong et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2016)

Proceedings Paper Computer Science, Artificial Intelligence

Sparse Recovery of Hyperspectral Signal from Natural RGB Images

Boaz Arad et al.

COMPUTER VISION - ECCV 2016, PT VII (2016)

Proceedings Paper Computer Science, Artificial Intelligence

Unsupervised Simultaneous Orthogonal Basis Clustering Feature Selection

Dongyoon Han et al.

2015 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (2015)

Article Engineering, Electrical & Electronic

Hyperspectral Imagery Super-Resolution by Spatial-Spectral Joint Nonlocal Similarity

Yongqiang Zhao et al.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2014)

Article Engineering, Electrical & Electronic

Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches

Jose M. Bioucas-Dias et al.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2012)

Article Geochemistry & Geophysics

Hyperspectral subspace identification

Jose M. Bioucas-Dias et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2008)

Article Engineering, Electrical & Electronic

K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation

Michal Aharon et al.

IEEE TRANSACTIONS ON SIGNAL PROCESSING (2006)

Article Geochemistry & Geophysics

Kernel-based methods for hyperspectral image classification

G Camps-Valls et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2005)

Article Computer Science, Artificial Intelligence

Image quality assessment: From error visibility to structural similarity

Z Wang et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2004)

Article Geochemistry & Geophysics

Comparison of airborne hyperspectral data and EO-1 Hyperion for mineral mapping

FA Kruse et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2003)

Article Geochemistry & Geophysics

Preprocessing EO-1 Hyperion hyperspectral data to support the application of agricultural indexes

B Datt et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2003)

Article Engineering, Electrical & Electronic

Spectral unmixing

N Keshava et al.

IEEE SIGNAL PROCESSING MAGAZINE (2002)