HYPERSPECTRAL IMAGE SUPER-RESOLUTION VIA CONVOLUTIONAL NEURAL NETWORK

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Author(s)

  • Shaohui Mei
  • Xin Yuan
  • Jingyu Ji
  • Shuai Wan
  • Qian Du

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publication2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings
PublisherIEEE
Pages4297-4301
ISBN (Electronic)9781509021758
Publication statusPublished - Sep 2017

Publication series

NameIEEE International Conference on Image Processing, ICIP
PublisherIEEE
ISSN (Print)1522-4880
ISSN (Electronic)2381-8549

Conference

Title24th IEEE International Conference on Image Processing, ICIP 2017
LocationChina National Convention Center
PlaceChina
CityBeijing
Period17 - 20 September 2017

Abstract

Due to the tradeoff between spatial and spectral resolution in remote sensing imaging, hyperspectral images are often acquired with a relative low spatial resolution, which limits their applications in many areas. Inspired by recent achievements in convolutional neural network (CNN) based super resolution (SR), a novel CNN based framework is constructed for SR of hyperspectral images by considering both spatial context and spectral correlation. As a result, the spectral distortion incurred by directly applying traditional SR algorithms to hyperspectral images is alleviated. Experimental results on several benchmark hyperspectral datasets have demonstrated that higher quality of reconstruction and spectral fidelity can be achieved, compared to band-wise manner based algorithms.

Research Area(s)

  • Convolutional neural network, Deep learning, Hyperspectral, Super-resolution

Citation Format(s)

HYPERSPECTRAL IMAGE SUPER-RESOLUTION VIA CONVOLUTIONAL NEURAL NETWORK. / Mei, Shaohui; Yuan, Xin; Ji, Jingyu; Wan, Shuai; Hou, Junhui; Du, Qian.

2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings. IEEE, 2017. p. 4297-4301 (IEEE International Conference on Image Processing, ICIP).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review