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IEEE Transactions on Image Processing, 2020
Due to hardware limitations of the imaging sensors, it is challenging to acquire images of high resolution in both spatial and spectral domains. Fusing a low-resolution hyperspectral image (LR-HSI) and a high-resolution multispectral image (HR-MSI) to ...
Zhengjue Wang +5 more
semanticscholar +1 more source
Due to hardware limitations of the imaging sensors, it is challenging to acquire images of high resolution in both spatial and spectral domains. Fusing a low-resolution hyperspectral image (LR-HSI) and a high-resolution multispectral image (HR-MSI) to ...
Zhengjue Wang +5 more
semanticscholar +1 more source
On a Variational Problem from Image Processing
2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
David, Guy, Semmes, Stephen
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Structure-Texture Image Decomposition Using Deep Variational Priors
IEEE Transactions on Image Processing, 2019Most variational formulations for structure-texture image decomposition force the structure images to have small norm in some functional spaces and to share a common notion of edges, i.e., large-gradients or large-intensity differences.
Youngjung Kim +3 more
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3D image processing for mitochondria morphology variation analysis
2014 IEEE International Symposium on Bioelectronics and Bioinformatics (IEEE ISBB 2014), 2014Mitochondria play an important role in producing energy of cell, aging and cell death. Previous investigations suggest that mitochondrial dysfunctions are associated with neurodegenerative, and the peripheral blood cells of those patients have validation of mitochondrial morphology.
null Han-Wei Dan +3 more
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End-to-End Variational Networks for Accelerated MRI Reconstruction
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2020The slow acquisition speed of magnetic resonance imaging (MRI) has led to the development of two complementary methods: acquiring multiple views of the anatomy simultaneously (parallel imaging) and acquiring fewer samples than necessary for traditional ...
Anuroop Sriram +7 more
semanticscholar +1 more source
Variational Methods in Image Processing
2018A short review is given on the rationale for using cost functions and optimization methods for modeling image processing and computer vision problems. Classical examples of various costs and functionals are given, illustrating this highly effective algorithmic approach. We examine different mathematical models Sects.
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Variational PDE models in image processing.
2003Summary: How can one restore a damaged picture? The authors discuss some recent applications of partial differential equations to such problems of image manipulation.
Chan, Tony F. +2 more
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Pre-Processing for Image Sequence Visualization Robust to Illumination Variations
2012Several images (a sequence) may be used to obtain better image quality. This method is perfect for super-resolution algorithms, which improve sub-pixel clarity of the image and allow a more detailed view. It is possible that illumination variations, e.g. those caused by a light source, lessen the benefits of super-resolution algorithms.
Šoda, Joško +3 more
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Total Variation Processing of Images with Poisson Statistics
2009This paper deals with denoising of density images with bad Poisson statistics (low count rates), where the reconstruction of the major structures seems the only reasonable task. Obtaining the structures with sharp edges can also be a prerequisite for further processing, e.g. segmentation of objects.
Alex Sawatzky +3 more
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