LOFAR sparse image reconstruction [PDF]
Context. The LOw Frequency ARray (LOFAR) radio telescope is a giant digital phased array interferometer with multiple antennas distributed in Europe. It provides discrete sets of Fourier components of the sky brightness. Recovering the original brightness distribution with aperture synthesis forms an inverse problem that can be solved by various ...
A. W. Gunst+89 more
openaire +17 more sources
Image reconstruction in optical interferometry [PDF]
Comment: accepted for publication in IEEE Signal Processing ...
Thiébaut, Eric+1 more
openaire +6 more sources
On Hallucinations in Tomographic Image Reconstruction [PDF]
Tomographic image reconstruction is generally an ill-posed linear inverse problem. Such ill-posed inverse problems are typically regularized using prior knowledge of the sought-after object property.
Sayantan Bhadra+3 more
semanticscholar +6 more sources
Optimizing computed tomography image reconstruction for focal hepatic lesions: Deep learning image reconstruction vs iterative reconstruction [PDF]
Background: Deep learning image reconstruction (DLIR) is a novel computed tomography (CT) reconstruction technique that minimizes image noise, enhances image quality, and enables radiation dose reduction.
Varin Jaruvongvanich+10 more
doaj +2 more sources
Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstruction [PDF]
Hyperspectral image (HSI) reconstruction aims to recover the 3D spatial-spectral signal from a 2D measurement in the coded aperture snapshot spectral imaging (CASSI) system.
Yuanhao Cai+7 more
semanticscholar +1 more source
RealFusion 360° Reconstruction of Any Object from a Single Image [PDF]
We consider the problem of reconstructing a full 360° photographic model of an object from a single image of it. We do so by fitting a neural radiance field to the image, but find this problem to be severely ill-posed.
Luke Melas-Kyriazi+3 more
semanticscholar +1 more source
Review of Super-Resolution Image Reconstruction Algorithms [PDF]
In human visual perception system, high-resolution (HR) image is an important medium to clearly express its spatial structure, detailed features, edge texture and other information, and it has a very wide range of practical value in medicine, criminal ...
ZHONG Mengyuan, JIANG Lin
doaj +1 more source
Measurement-conditioned Denoising Diffusion Probabilistic Model for Under-sampled Medical Image Reconstruction [PDF]
We propose a novel and unified method, measurement-conditioned denoising diffusion probabilistic model (MC-DDPM), for under-sampled medical image reconstruction based on DDPM.
Yutong Xie, Quanzheng Li
semanticscholar +1 more source
Review of Image Super-resolution Reconstruction Algorithms Based on Deep Learning [PDF]
The essence of image super-resolution reconstruction technology is to break through the limitation of hardware conditions, and reconstruct a high-resolution image from a low-resolution image which contains less infor-mation through the image super ...
YANG Caidong, LI Chengyang, LI Zhongbo, XIE Yongqiang, SUN Fangwei, QI Jin
doaj +1 more source
NeRP: Implicit Neural Representation Learning With Prior Embedding for Sparsely Sampled Image Reconstruction [PDF]
Image reconstruction is an inverse problem that solves for a computational image based on sampled sensor measurement. Sparsely sampled image reconstruction poses additional challenges due to limited measurements. In this work, we propose a methodology of
Liyue Shen, J. Pauly, Lei Xing
semanticscholar +1 more source