21 papers · ranked by Valyu relevance
Thomas P. Watson, Eddie L. Jacobs
—Hyperspectral cameras provide numerous advantages in terms of the utility of the data captured. They capture hundreds of data points per sample (pixel) instead of only the few of RGB or multispectral camera systems. Aerial systems sense such data remotely, but the data must be georectified to produce consistent images…
John K. Delaney, Kathryn A. Dooley, Roxanne Radpour, Ioanna Kakoulli
Macroscale multimodal chemical imaging combining hyperspectral diffuse reflectance (400-2500 nm), luminescence (400-1000 nm), and X-ray fluorescence (XRF, 2 to 25 keV) data, is uniquely equipped for noninvasive characterization of heterogeneous complex systems such as paintings. Here we present the first application of…
Deependra Mishra, Helena Hurbon, John Wang, Steven T. Wang + 13 more
'Tommy Du' 'Qian Wu' 'David Kim' 'Shiva Basir' 'Qian Cao' 'Hairong Zhang' 'Kathleen Xu' 'Andy Yu' 'Yifan Zhang' 'Yunshen Huang' 'Roman Garnett' 'Maria Gerasimchuk-Djordjevic' 'Mikhail Y. Berezin'] Multi- and hyperspectral imaging modalities encompass a growing number of spectral techniques that find many applications…
Peichao Li, Michael Ebner, Philip Noonan, Conor Horgan + 4 more
'Sébastien Ourselin' 'Jonathan Shapey' 'Tom Vercauteren'] Title: ABSTRACT Hyperspectral imaging is one of the most promising techniques for intraoperative tissue characterisation. Snapshot mosaic cameras, which can capture hyperspectral data in a single exposure, have the potential to make a real-time hyperspectral…
Cinmayii A. Garillos-Manliguez, John Y. Chiang, Marc Brecht
Fruit maturity is a critical factor in the supply chain, consumer preference, and agriculture industry. Most classification methods on fruit maturity identify only two classes: ripe and unripe, but this paper estimates six maturity stages of papaya fruit. Deep learning architectures have gained respect and brought…
Shixin Huang, Jiawei Luo, Kexue Pu, Min Wu
Hepatobiliary tumor is one of the common tumors and cancers in medicine, which seriously affects people's lives, so how to accurately diagnose it is a very serious problem. This article mainly studies a diagnostic method of microscopic images of liver and gallbladder tumors. Under this research direction, this article…
Dimitra Koumoutsou, Eleni Charou, Georgios Siolas, Giorgos Stamou
This paper introduces the Class-wise Principal Component Analysis, a supervised feature extraction method for hyperspectral data. Hyperspectral Imaging (HSI) has appeared in various fields in recent years, including Remote Sensing. Realizing that information extraction tasks for hyperspectral images are burdened by…
Vytautas Paura, Virginijus Marcinkevičius
Adapted U-Net Architecture Authors: ['Vytautas Paura' 'Virginijus Marcinkevičius'] Abstract. The hyperspectral unmixing method is an algorithm that extracts material (usually called endmember) data from hyperspectral data cube pixels along with their abundances. Due to a lower spatial resolution of hyperspectral…
Lufan Xie, Lijing Zhang, Fan Yang, Mengchen Lin + 7 more
Traditional hyperspectral cameras transmit full data cubes to host computers, creating severe bandwidth and storage bottlenecks that impede real-time analysis. We present a Zynq-7035-based intelligent camera using hardware-software codesign to enable on-board processing and transmit only actionable results. This…
Tianzhen Ma, Zhijing He, Bin Wu, Yutian Lei + 9 more
Highlights What are the main findings?1. A divided-aperture snapshot thermal infrared multispectral camera is developed, enabling single-exposure acquisition of both thermal images and multispectral data, with precise sub-channel image registration achieved via a star-point array calibration method. 2. A neural…
Laura J. Brooks, Daniel Pearce, Kenton Kwok, Nikhil Jawade + 8 more
Hyperspectral cameras are a key enabling technology in precision agriculture, biodiversity monitoring, and ecological research. Consequently, these applications are fuelling a growing demand for devices that are suited to widespread deployment in such environments. Current hyperspectral cameras, however, require…
Uphar Singh, Tushar Musale, Ranjana Vyas, O. P. Vyas
Hyper-spectral images are images captured from a satellite that gives spatial and spectral information of specific region.A Hyper-spectral image contains much more number of channels as compared to a RGB image, hence containing more information about entities within the image. It makes them well suited for the…
Sripad Ram
We present a general stochastic model for hyperspectral imaging data and derive analytical expressions for the Fisher information matrix for the underlying spectral unmixing problem. We investigate the linear mixing model as a special case and define a linear unmixing performance bound by using the Cramer-Rao…
Yina Wang, Bin Yang, Siyu Feng, Veronica Pessino + 1 more
Hyperspectral imaging is a powerful technique to simultaneously study multiple fluorophore labels with overlapping emissions. Here we present a computational hyperspectral imaging method, which uses the sample spatial fluorescence information as a reconstruction constraint. Our method addresses both the under-sampling…
Neetu Sigger, Tuan T. Nguyen, Gianluca Tozzi
Advancements in biomedical imaging have increasingly explored innovative models for studying human skin conditions. Recent research highlights a biochemical connection between banana peels and human skin, particularly through the enzyme tyrosinase, which plays a key role in pigmentation and oxidative stress. Studies…
Neetu Sigger, Tuan Thanh Nguyen, Sadaf Ashraf, Gianluca Tozzi
Hyperspectral imaging (HSI) has gained increasing attention for bone assessment because it captures rich wavelength dependent information associated with mineralised tissue. HSI provides detailed spectral information related to material composition, while 3D geometric information supports the analysis of surface…
Nafiseh Ghasemi, Jon Alvarez Justo, Marco Celesti, L. Despoisse + 1 more
'Jens Nieke'] Recent advancements in deep learning techniques have spurred considerable interest in their application to hyperspectral imagery processing. This paper provides a comprehensive review of the latest developments in this field, focusing on methodologies, challenges, and emerging trends. Deep learning…
Authors not listed
nDTomo is a Python-based software suite for the simulation, reconstruction and analysis of X-ray chemical imaging and computed tomography data. It provides a collection of Python function-based tools designed for accessibility and education as well as a graphical user interface (GUI). Prioritising transparency and ease…
Ioannis Kavouras, Ioannis Rallis, Nikolaos Doulamis, Anastasios Doulamis
climate change monitoring over the port areas Authors: ['Ioannis Kavouras' 'Ioannis Rallis' 'Nikolaos Doulamis' 'Anastasios Doulamis'] The environmental hazards and climate change effects causes serious problems in land and coastal areas. A solution to this problem can be the periodic monitoring over critical areas…
Alexander E. Siemenn, Eunice Aissi, Fang Sheng, Armi Tiihonen + 3 more
In materials research, the task of characterizing hundreds of different materials traditionally requires equally many human hours spent measuring samples one by one. We demonstrate that with the integration of computer vision into this material research workflow, many of these tasks can be automated, significantly…
Dimitar Georgiev, Simon Vilms Pedersen, Ruoxiao Xie, Álvaro Fernández-Galiana + 2 more
Raman spectroscopy is a non-destructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by the lack of software, methodological and data standardisation, and the…