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Bayesian based MF-SR (multi-frame superresolution) has been used as a popular and effective SR model. However, texture region is not reconstructed sufficiently because it works on the spatial domain. In this paper, we extend the MF-SR method to operate on the frequency domain for the improvement of HF information as much as possible. For this, we propose a spatially weighted bilateral total variation...
The noise in a low-radiation dose can be enhanced by an iterative reconstruction technique using forward and back projection models. This work investigated an iterative reconstruction approach using a forward projection model based on a contrast limited adaptive histogram equalization (CLAHE). Using the CLAHE technique, the projection image was processed to remove the noise, and then the preprocessed...
Granulation segmentation of the solar photosphere is important step to obtain correct morphometric measures. In this paper, we present a novel method, using morphological technique, for granules segmentation in the solar photosphere. Firstly, a morphological filtering, employing opening-by-reconstruction and closing-by-reconstruction, is used to eliminate image noise. Secondly, Otsu technique is implemented...
Building high dynamic range (HDR) images by combining photographs captured with different exposure times present several drawbacks, such as the need for global alignment and motion estimation in order to avoid ghosting artifacts. The concept of spatially varying pixel exposures (SVE) proposed by Nayar et al. enables to capture in only one shot a very large range of exposures while avoiding these limitations...
We introduce the Imperial College London and National University of Ireland Maynooth (ICL-NUIM) dataset for the evaluation of visual odometry, 3D reconstruction and SLAM algorithms that typically use RGB-D data. We present a collection of handheld RGB-D camera sequences within synthetically generated environments. RGB-D sequences with perfect ground truth poses are provided as well as a ground truth...
The tomographic image of a single cylindrical PEC object is obtained using diffraction tomography theorem after multiple transmissions of independent and identically distributed (iid) UWB random noise waveforms. The final tomographic image of the cylinder is successfully achieved by averaging all obtained images from multiple transmissions. For each transmission, iid band-limited white Gaussian noise...
Computed Tomography (CT) scanners evolved from simple parallel-beam geometry into more complex fan-beam geometry. The rebinning mechanism to convert fan-beam projections to parallel-beam projections is one of the methods simplifying the reconstruction of the CT image. Various interpolation methods result in different numerical presentations and noisy textures in the reconstructed CT images. This paper...
Compressive Sensing (CS) was originally developed to directly acquire a compressed description of a sparse scene. This can be possible provided that the sampling scheme meet certain criteria. In Radar applications, the main advantage highlighted in the literature is the reduction of the data-flow between the R.F. front-end and processing that would be intractable in number of cases. However thanks...
Image super resolution (SR) reconstruction technique is receiving increasing attention from the image processing community, and it has been widely used in many applications such as remote sensing image, medical image, video surveillance and high definition television. The essential of image SR reconstruction technique is how to produce a clearly high resolution (HR) image from the information of one...
Electrical Impedance Tomography (EIT) is a noninvasive tomographic imaging modality, where cross-sectional images of conductivity and/or permittivity distribution inside of a volume are reconstructed. Electrical Impedance and Diffused Optical Reconstruction Software (EIDORS) is used in this tomographic imaging. In this paper, simulation is carried out in two different conditions and using simulated...
This paper proposes a simulation environment for creating simulated ranging data of high resolution sonar systems. It enables the assessment of underwater object reconstruction techniques and the verification of various methods for automated target detection. As an input, the proposed environment uses the AUV's trajectory, a model of the sonar system attached to the AUV and 3D CAD models of underwater...
Computed Tomography as well as Magnetic Resonance or Positron Electron Tomography are currently the most commonly used medical imaging modalities for the analysis of human body complex structures and organs, where diseases must be recognized and identified. The image reconstruction process used in these tomography techniques is usually based on the Radon Transform (RT). In this paper, an algorithm...
Penalized likelihood (PL) image reconstruction has been developed for emission tomography to improve the image quality of reconstructed images. One challenge in PL reconstruction is that the selection of a proper regularization parameter to achieve a balance between the likelihood function and penalty function can be difficult. Here we present a novel method to choose the regularization parameter...
In this paper, an improved method of constructing FBP2D (3D) based variance map is introduced and implemented successfully. Accordingly, a quadratic version of distance driven back-projector (DD) compatible with variance reconstruction is developed to exploit fully the features of DD. As a result, the calculated variance is validated and shows an excellent match with ground truth.
We propose a new model for the reconstruction of biological structures using Multiple-Angle Total Internal Reflection Fluorescence Microscopy (MA-TIRFM). This recent microscopy technique allows the visualization of sub-cellular structures around the plasma membrane which is of fundamental importance in the comprehension of exchanges mechanisms of the cell. We present a 3D reconstruction method based...
Incorporating anatomical information obtained by magnetic resonance (MR) imaging has shown its promises to improve the positron emission tomography (PET) imaging quality. In this paper, we propose a novel maximum a posteriori (MAP) PET image reconstruction technique using a sparse prior whose dictionary is learned from the corresponding MR images. Specifically, a PET image is divided into three-dimensional...
Low-dose x-ray computed tomography (CT) scan is clinically desired. However, the quality of low-dose CT image is severely degraded due to excessive photon quantum noise and electronic noise. To improve the quality of CT image with lower milliampere-seconds (mAs), in this study, we developed an iterative image reconstruction algorithm based on the maximum a posterior (MAP) principle. To preserve the...
Incorporating the point spread function (PSF) into the iterative MLEM reconstruction of PET images introduces contrast and size dependent ringing and over enhancement artifacts. We previously developed a new method, called TV-PSF-MLEM, to suppress these artifacts based on the introduction of a locally-weighted total variation regularization within the MLEM reconstruction algorithm. On non-noisy PET...
High radiation dose during x-ray computed tomography (CT) examinations can increase the risk of cancer and has become major concerns to patient. Accordingly, minimizing the radiation exposure without sacrificing image quality is a meaningful research topic. In this work, with the aim to reduce radiation during data acquisition, we propose a penalized weighted least-squares (PWLS) scheme to retain...
Imaging the bioelectrical source distribution along the infarct border is of important therapeutic potential as infarct border is the common site for reentry circuits leading to life-threatening arrhythmias. Although it can be tackled by computational reconstruction of volumetric cardiac source using body-surface voltage data, the problem is notoriously ill-posed without a unique solution. Progress...
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