Results 31 to 40 of about 16,943 (161)

PANSHARPENING OF HYPERSPECTRAL IMAGES IN URBAN AREAS [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012
Pansharpening has proven to be a valuable method for resolution enhancement of multi-band images when spatially high-resolving panchromatic images are available in addition. In principle, pansharpening can beneficially be applied to hyperspectral images
C. Chisense, J. Engels, M. Hahn, E. Gülch   +3 more
doaj   +1 more source

Cancer cytoplasm segmentation in hyperspectral cell image with data augmentation

Informatics in Medicine Unlocked
Hematoxylin and Eosin (H&E)-stained images are commonly used to detect nuclear or cancerous regions in cells from images captured by a microscope. Identifying cancer cytoplasm is crucial for determining the type of cancer; hence, obtaining accurate ...
Rebeka Sultana, Hibiki Horibe, Tomoaki Murakami, Ikuko Shimizu   +3 more
doaj   +1 more source

Spectral uncertainty analysis of grassland and its camouflage materials based on land-based hyperspectral images

Open Physics, 2023
Spectral uncertainty is one of the most prominent spectral characteristics of hyperspectral images. Compared to the process of remote sensing hyperspectral imaging, hyperspectral imaging under land-based imaging conditions has the characteristics of ...
Zhao Jiale, Zhou Bing, Wang Guanglong, Liu Jie, Ying Jiaju, Chen Qi, Zhao Runze   +6 more
doaj   +1 more source

A New Vegetation Index in Short-Wave Infrared Region of Electromagnetic Spectrum

IEEE Access, 2021
Vegetation index algorithms based on radiance and/or reflectance data in the Visible Near Infrared (VNIR) band are created for multispectral and hyperspectral images to detect vegetation.
Yucel Cimtay, Busra Ozbay, Gokce Nur Yilmaz, Eda Bozdemir   +3 more
doaj   +1 more source

Hyperspectral Neural Radiance Field Method Based on Reference Spectrum

IEEE Access
The Neural Radiance Field (NeRF) method for datasets is gaining attention for its wide applications and research value. Hyperspectral images have also gained many applications in recent years.
Runchuan Ma, Sailing He
doaj   +1 more source

Hyperspectral Image Super-Resolution Algorithm Based on Graph Regular Tensor Ring Decomposition

Remote Sensing, 2023
This paper introduces a novel hyperspectral image super-resolution algorithm based on graph-regularized tensor ring decomposition aimed at resolving the challenges of hyperspectral image super-resolution.
Shasha Sun, Wenxing Bao, Kewen Qu, Wei Feng, Xiaowu Zhang, Xuan Ma   +5 more
doaj   +1 more source

Novel View Synthesis and Dataset Augmentation for Hyperspectral Data Using NeRF

IEEE Access
Hyperspectral data for the 3D domain is relatively difficult to acquire. Existing hyperspectral datasets are unsuitable for 3D research, suffer from issues of severe data scarcity, and a lack of multi-perspective images of the same object, etc.
Runchuan Ma, Tengfei Ma, Deyu Guo, Sailing He   +3 more
doaj   +1 more source

Herschel vision: A hyperspectral image processing software for data preparation in machine learning pipelines

SoftwareX
In recent years, publications have relied on either commercial software or custom-developed codes for the analysis of hyperspectral images. This practice has inadvertently restricted the broader adoption of hyperspectral imaging.
Billy G. Ram, Sunil GC, Xin Sun
doaj   +1 more source

Deep Learning in Hyperspectral Image Reconstruction from Single RGB images—A Case Study on Tomato Quality Parameters

Remote Sensing, 2020
Hyperspectral imaging has many applications. However, the high device costs and low hyperspectral image resolution are major obstacles limiting its wider application in agriculture and other fields.
Jiangsan Zhao, Dmitry Kechasov, Boris Rewald, Gernot Bodner, Michel Verheul, Nicholas Clarke, Jihong Liu Clarke   +6 more
doaj   +1 more source

The Influence of Image Degradation on Hyperspectral Image Classification

Remote Sensing, 2022
Recent advances in hyperspectral remote sensing techniques, especially in the hyperspectral image classification techniques, have provided efficient support for recognizing and analyzing ground objects.
Congyu Li, Zhen Li, Xinxin Liu, Shutao Li   +3 more
doaj   +1 more source