Results 251 to 260 of about 98,568 (293)
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Snapshot hyperspectral imaging
Integrated Computational Imaging Systems, 2001Hyperspectral imaging associates a densely sampled spectral signature with each pixel in an imager’s field of view. The collected image data are in the form of a three-dimensional data set, i.e., an image cube. The image cube is also referred to as a hypercube or an object cube.
M.R. Descour +5 more
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2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), 2015
In this work we propose a new formulation for hyperspectral denoising based on the Blind Compressed Sensing (BCS) framework. BCS learns the sparsifying basis during signal recovery combining the advantages of standard sparse recovery with dictionary learning. We show that our proposed formulation yields better results than a state-of-the- art technique
Hemant Kumar Aggarwal, Angshul Majumdar
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In this work we propose a new formulation for hyperspectral denoising based on the Blind Compressed Sensing (BCS) framework. BCS learns the sparsifying basis during signal recovery combining the advantages of standard sparse recovery with dictionary learning. We show that our proposed formulation yields better results than a state-of-the- art technique
Hemant Kumar Aggarwal, Angshul Majumdar
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On the characterization of hyperspectral texture
IEEE International Geoscience and Remote Sensing Symposium, 2003Many tools have been proposed in the literature for texture characterization of images. Some of them are based on statistical properties, others on fractal measures and some more on multiresolution analysis. Those methods have been proposed in a scalar point of view to be applied on mono-band images.
Grégoire Mercier, Marc Lennon
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Spaceborne Hyperspectral Image Generation based on Airborne Hyperspectral Image
IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008In order to support spaceborne hyperspectral sensor system design, an end-to-end simulation model for spaceborne hyperspectral image generation starting from the airborne image has been developed in this paper. Airborne image after being resampled both in the space and spectrum performs as the at-sensor radiance that is the input of the sensor model ...
Junping Zhang +3 more
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Miniature hyperspectral systems
2017Spectroscopy methods have been used for decades to obtain information about various materials, ranging from galaxies billions of light years from earth, to Petri dishes containing rich bacteria cultures. From spectrometers in chemical labs to spectral cameras on satellites, the high dimensionality of spectral data is proven to be an excellent source of
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Hyperspectral Band Selection Based on Endmember Dissimilarity for Hyperspectral Unmixing
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018Hyperspectral remote sensing could acquire hundreds of bands to cover a complete spectral interval, which deliver more information and allow a whole range of new and more precise applications. But vast data volume can cause trouble in computer processing and data transmission.
Mingming Xu 0001 +6 more
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Hyperspectral In-Memory Computing
Optical Fiber Communication Conference (OFC) 2024We propose and demonstrate hyperspectral in-memory computing systems that harness both frequency and space dimensions, utilizing optical frequency combs and programmable optical memories. This approach offers the potential for energy-efficient optical information processing beyond PetaOPS-level performance.
Mostafa Honari-Latifpour +3 more
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IEEE Transactions on Geoscience and Remote Sensing, 2017
Matthew Ferrara +2 more
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Matthew Ferrara +2 more
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A Review of Deep Learning Used in the Hyperspectral Image Analysis for Agriculture
Artificial Intelligence Review, 2021Ping Liu, Xiang Li, Jialin Hou
exaly
Hyperspectral-Cube-Based Mobile Face Recognition: A Comprehensive Review
Information Fusion, 2021Haitao Zhao, Xianyi Zhang
exaly