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A Parallel Computing Paradigm for Pan-Sharpening Algorithms of Remotely Sensed Images on a Multi-Core Computer

Jinghui Yang, Jixian Zhang, Guoman Huang
2014 Remote Sensing  
This paper presents a parallel computing paradigm for pan-sharpening algorithms based on a generalized fusion model and parallel computing techniques.  ...  adopted, in the best cases the fastest times required to finish the entire fusion operation (including disk input/output (I/O) and computation) are close to the time required to directly read and write the images  ...  The parallel computing approach makes it possible for multiple blocks to be processed concurrently on multiple CPU cores.  ... 
doi:10.3390/rs6076039 fatcat:zqtaqrp565adfjxtjfaygyfauy

Advances in Hyperspectral Image and Signal Processing: A Comprehensive Overview of the State of the Art

Pedram Ghamisi, Naoto Yokoya, Jun Li, Wenzhi Liao, Sicong Liu, Javier Plaza, Behnood Rasti, Antonio Plaza
2017 IEEE Geoscience and Remote Sensing Magazine  
Hence, rigorous and innovative methodologies are required for hyperspectral image and signal processing and have become a center of attention for researchers worldwide.  ...  Recent advances in airborne and spaceborne hyperspectral imaging technology have provided end users with rich spectral, spatial, and temporal information, which make a plethora of applications for the  ...  In addition, the authors would like to thank the National Center for Airborne Laser Mapping (NCALM) at the University of Houston for providing the CASI Houston data set, and the IEEE GRSS Image Analysis  ... 
doi:10.1109/mgrs.2017.2762087 fatcat:6ezzye7yyvacbouduqv2f2c7gi

A PROPOSED FRAMEWORK TO UNMIX SCATTERING MECHANISMS OF POLARIMETRIC RADAR IMAGES USING VERY HIGH RESOLUTION OPTICAL IMAGES

S. Giordano, G. Mercier, J.-P. Rudant
2012 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
A new approach has been proposed for radar and optical image fusion. Candidate images for fusion are polarimetric radar images and very high resolution stereoscopic optical images.  ...  In the first part of this paper, observation-based state-of-the-art methods for optical and radar image fusion are discussed.  ...  For IHS and PCA transforms, the end of the algorithm is an inverse transformation that retrieves R, G, B values of the sharpened product.  ... 
doi:10.5194/isprsannals-i-7-279-2012 fatcat:mwil4wtddjbb3gbwfyw67zozsy

Performance Analysis Of Brain Tumor Detection Based On Image Fusion

S. Anbumozhi, P. S. Manoharan
2014 Zenodo  
The texture and wavelet features are extracted from the fused image. The multilevel Adaptive Neuro Fuzzy Classifier classifies the brain tumors based on trained and tested features.  ...  Experimental results obtained from fusion process prove that the use of the proposed image fusion approach shows better performance while compared with conventional fusion methodologies.  ...  In this paper, wavelet transform, principle component analysis (PCA) and Fuzzy Logic techniques are utilized for fusing these two images and results are compared.  ... 
doi:10.5281/zenodo.1093490 fatcat:6lxfxm5ydvhhzogyltkq7drmhi

PERFORMANCE ANALYSIS OF HIGH EFFICIENT AND LOW POWER ARCHITECTURE FOR FUZZY BASED IMAGE FUSION

Anbumozhi
2014 American Journal of Applied Sciences  
Image fusion based on wavelet transform is the most commonly used image fusion method, which fuses the source images' information in wavelet domain according to some fusion rules.  ...  The hardware architecture for fuzzy based image fusion is proposed. This proposed hardware architecture reduces the hardware utilizations and best suitable for low power applications.  ...  For the construction of 2×2 sub block, the edge pixel is noted if any pixel variation occurs in this sub-block.  ... 
doi:10.3844/ajassp.2014.769.781 fatcat:gqhi6plxmjg4npke2zkcdaoc54

Multiscale Feature Extraction based on Convolutional Sparse Decomposition for Hyperspectral Image Classification

Chongxiao Zhong, Junping Zhang, Ye Zhang
2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
For example, the 3D wavelet transform [29] and 3D Gabor filter [30] designed for multiscale spatial feature extraction have both achieved decent results, and several classification approaches have  ...   Abstract-Due to the different spatial properties presented by various ground objects in hyperspectral image (HSI), multiscale-based feature extraction approaches have been developed for HSI classification  ... 
doi:10.1109/jstars.2020.3019300 fatcat:76xu6pgrofdbdjf6hrrwun3gay

Hyperspectral Image Super-Resolution with 1D–2D Attentional Convolutional Neural Network

Jiaojiao Li, Ruxing Cui, Bo Li, Rui Song, Yunsong Li, Qian Du
2019 Remote Sensing  
The hyperspectral single image super-resolution (HSISR) task is correspondingly difficult in SR due to the unavailability of auxiliary high resolution images.  ...  Hyperspectral image (HSI) super-resolution (SR) is of great application value and has attracted broad attention.  ...  For each dataset, a 144 × 144 sub-region is selected to evaluate the performance of our proposed 1D-2D attentional CNN, another 144 × 144 sub-region is selected for verication, while the remaining are  ... 
doi:10.3390/rs11232859 fatcat:btvw2fyv4vbs7oqzwjrj6n2uj4

An investigation of image fusion algorithms using a visual performance-based image evaluation methodology

Kelly E. Neriani, Alan R. Pinkus, David W. Dommett, Ivan Kadar
2008 Signal Processing, Sensor Fusion, and Target Recognition XVII  
Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching data sources, gathering and maintaining  ...  Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to  ...  A novel method based on discrete multiple wavelet transform to multispectral image fusion.  ... 
doi:10.1117/12.779752 fatcat:plise3knpvalvfky6ei5lahk5u

A survey of classical methods and new trends in pansharpening of multispectral images

Israa Amro, Javier Mateos, Miguel Vega, Rafael Molina, Aggelos K Katsaggelos
2011 EURASIP Journal on Advances in Signal Processing  
Finally we analyze how the quality of the pansharpened images can be assessed both visually and quantitatively and examine the different quality measures proposed for that purpose.  ...  There exist a number of satellites on different earth observation platforms, which provide multispectral images together with a panchromatic image, that is, an image containing reflectance data representative  ...  The discrete approach of the wavelet transform, named Discrete Wavelet Transform (DWT), can be performed using several different approaches, probably the most popular ones for image pansharpening being  ... 
doi:10.1186/1687-6180-2011-79 fatcat:zdepdfpt4bevjfbr2k6f5ljd4e

Front Matter: Volume 10033

2016 Eighth International Conference on Digital Image Processing (ICDIP 2016)  
Publication of record for individual papers is online in the SPIE Digital Library. SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model.  ...  method for block ambiguities of independent component analysis using previous demixing matrices [10033-242] 10033 55 Artifact removal for physiological signals via wavelets [10033-153] xii Proc  ...  -141] 10033 29 Fast single image defogging method based on physical model [10033-30] 10033 2A An improved unsharp masking sharpening algorithm for image enhancement [10033-35] SESSION 7 IMAGE  ... 
doi:10.1117/12.2257252 fatcat:v2ipfp2mp5gedjypzpecahpo7e

Deep Learning Meets Hyperspectral Image Analysis: A Multidisciplinary Review

Alberto Signoroni, Mattia Savardi, Annalisa Baronio, Sergio Benini
2019 Journal of Imaging  
Deep learning approaches certainly offer a great variety of opportunities for solving classical imaging tasks and also for approaching new stimulating problems in the spatial–spectral domain.  ...  Modern hyperspectral imaging systems produce huge datasets potentially conveying a great abundance of information; such a resource, however, poses many challenges in the analysis and interpretation of  ...  Conversely, in [82] modified sparse denoising AEs were used to train a mapping between low-resolution and high-resolution image patches for pan-sharpening.  ... 
doi:10.3390/jimaging5050052 pmid:34460490 fatcat:ledlmt42bfdtdhe7tvj2dl2rwm

Machine Learning Techniques and Applications For Ground-based Image Analysis [article]

Soumyabrata Dev, Bihan Wen, Yee Hui Lee, Stefan Winkler
2016 arXiv   pre-print
The images captured by whole sky imagers can have high spatial and temporal resolution, which is an important pre-requisite for applications such as solar energy modeling, cloud attenuation analysis, local  ...  Ground-based whole sky cameras have opened up new opportunities for monitoring the earth's atmosphere.  ...  One such example is hyperspectral image classification [77] . In addition to SSL methods, models involving sparsity and other regularized approaches are also becoming popular. For example, Tuia et al  ... 
arXiv:1606.02811v1 fatcat:k5n7u7lynzd4tciedcw54wdv2m

Ground-based image analysis: A tutorial on machine-learning techniques and applications

Soumyabrata Dev, Bihan Wen, Yee Hui Lee, Stefan Winkler
2016 IEEE Geoscience and Remote Sensing Magazine  
The images captured by whole sky imagers can have high spatial and temporal resolution, which is an important pre-requisite for applications such as solar energy modeling, cloud attenuation analysis, local  ...  Ground-based whole sky cameras have opened up new opportunities for monitoring the earth's atmosphere.  ...  One such example is hyperspectral image classification [74] . In addition to SSL methods, models involving sparsity and other regularized approaches are also becoming popular. For example, Tuia et al  ... 
doi:10.1109/mgrs.2015.2510448 fatcat:57pkeukq2jclxkz3q23fn5kn6e

Color-to-gray conversion using ISOMAP

Ming Cui, Jiuxiang Hu, Anshuman Razdan, Peter Wonka
2009 The Visual Computer  
This approach generalizes the gradient domain manipulation for high dimensional images.  ...  In this paper we present a new algorithm to transform an RGB color image to a grayscale image.  ...  [20] and visualization based on PCA [38] . Recent investigation suggest that nonlinearity exists in hyperspectral data [19] .  ... 
doi:10.1007/s00371-009-0412-7 fatcat:vytvsovkyvdrbk3375v34rdjzu

Toward Real Hyperspectral Image Stripe Removal via Direction Constraint Hierarchical Feature Cascade Networks

Chengjun Wang, Miaozhong Xu, Yonghua Jiang, Guo Zhang, Hao Cui, Guohui Deng, Zhongyuan Lu
2022 Remote Sensing  
In hyperspectral imaging (HSI), stripe noise is one of the most common noise types that adversely affects its application.  ...  However, it is difficult to obtain paired training samples for real data. Most CNN destriping methods construct a paired training dataset with simulated stripe noise for network training.  ...  ., Zhuhai (China) for providing the Chinese Zhuhai-1 data, the owners of the public HSI dataset, and the authors of the comparison methods used in this article for sharing their data and code.  ... 
doi:10.3390/rs14030467 fatcat:xz2t5cmzznfu3io5zpltav4btq
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