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Impulse noise corruption in digital images frequently occurs because of errors generated in noisy sensors or communication channels, such as faulty memory locations in devices, malfunctioning pixels within the camera, and bit errors in transmission. Although the recently developed big data streaming enhances the viability of video communication, visual distortions in images that are caused by impulse...
Plane wave ultrasound imaging (PW) with coherent compounding can improve the image quality in terms of contrast, SNR, and lateral resolution compared to the conventional PW method. When the number of PW transmissions is small, the image quality still need improvement. In this paper, we proposed to first estimate the synthetic transmit aperture imaging (STA) data with regularized singular-value decomposition...
EEG source imaging is able to reconstruct sources in the brain from scalp measurements with high temporal resolution. Due to the limited number of sensors, it is very challenging to locate the source accurately with high spatial resolution. Recently, several total variation (TV) based methods have been proposed to explore sparsity of the source spatial gradients, which is based on the assumption that...
We propose an approach to produce computer generated holograms (CGH) from RGBD data. Being able to produce CGH from RGBD images simplifies the recording process and results in more realistic reconstruction. A multilayer wavefront recording plane method is described for fast wave propagation, and it is completed with a two-step occlusion culling process to preserve the self-occlusion effect. The approach...
Measurement samples are often taken in various monitoring applications. To reduce the sensing cost, it is desirable to achieve better sensing quality while using fewer samples. Compressive Sensing (CS) technique finds its role when the signal to be sampled meets certain sparsity requirements. In this paper we investigate the possibility and basic techniques that could further reduce the number of...
In this work, a new topic, which is to synthesize (recover) the holograms between two or more recorded holograms with a large angle discrepancy, is presented. The technique aims at enlarging view angle, speeding up the recording process by reducing sensing points, and increasing resolution in holographic radar and light. Our method to tackle the problem is proposed. We analyze the problem in both...
This paper proposes an efficient and structure-based image/video (interframe independent) super resolution (SR) scheme. Image/video SR is currently a very active area of research because it is used in various applications. The basic idea of the proposed scheme is based on the concepts of pattern redundancy and parallel computing. Global and local motions of pixels are well estimated by exploiting...
This paper suggests a thin cloud removing approach of remote sensing image based on robust kernel regression. Due to the influence of atmosphere condition, cloud cover is one of the most disturbance factors in remote sensing image. So cloud removal is a very important step for improving the quality of the image before making analysis. Because thin cloud is the low frequency component in remote sensing...
Based on a deep discussion on the algorithm of multi-CCD sensor planning, genetic algorithm ant algorithm (GAAA) is proposed in this paper. GAAA is superior to ant colony algorithm in time efficiency and also superior to genetic algorithm in solution efficiency. Through optimizing, it improves the resulting efficiency of digital image processing greatly. moreover, it is more convenient to the latter...
Recent years LiDAR data is widely used for constructing 3D terrain models which provide realistic impressions of the urban environment. This paper presents an automatic method for extracting 3D building model by the fusion of LiDAR data, 2D building outlines and orthoimage. 2D building outlines is generated by classifying the LiDAR data to terrain and off-terrain points, then detecting building edges...
The prior of blocky resistivity profile is formulated based on the minimal of total variation using Bayesian method, and the resistivity distribution is reconstructed by Maximum a posteriori (MAP). The Markov chain Monte Carlo (MCMC) method with Gibbs sampler is used to sample from posterior density. The simulations on the 2D model show the feasibility of the method.
In MRI images, the boundary of each encephalic tissue is highly irregular. Sphere-Shaped Support Vector Machine (SSSVM) has the advantage of solving high non-linearity and irregularity problems. In this paper, SSSVM is applied in brain MRI image 3D reconstruction. Selecting parameters for SSSVM, however, is a complicated problem. Appropriate parameters can make the model more flexible and help to...
MITK supports an extensive set of image processing and volume rendering functionality, and it is a very convenient tool. 3-D reconstruction of the liver is performed by MITK under VC++ 6.0 platform. Compared with 3-D reconstruction results by Amira, good surface image of liver could be obtained by MITK. The 3-D reconstruction image of liver can be used for finite element analysis and temperature field...
Electrical impedance tomography (EIT) is a noninvasive technique that permits estimation of resistivity within a subject by reconstructing from boundary measurements. The head electrical properties based on EIT technology have been studied by many authors and in most of this work the realistic head model has been considered without contact impedance between the electrodes and the scalp. It is interesting...
The modified Newton-Raphson (MNR) method is used to solve the inverse resistivity problem in this paper. Using Tikhonov regularization method, comparisons among the L-curve method, the zero-crossing (ZC) method and the generalized cross validation (GCV) method are carried out for determining the regularization parameters of MNR method. By these criterions the appropriate regularization parameters...
Electrical impedance tomography (EIT) is a noninvasive technique to estimate the conductivity distribution inside the object. In EIT, driving currents are injected through the object and voltages are measured at the electrodes on the surface. Algorithms to estimate the conductivity distribution from the measured voltages are called reconstruction algorithms. Image reconstruction is a nonlinear inverse...
Three EIT approaches for static imaging of head are investigated in this paper. The modified Newton-Raphson (MNR) method and the differential evolution (DE) algorithm are applied to the impedance reconstruction of 2D section of head based on real head model. Comparisons are carried out on the results obtained using simulated data, and a DE-MNR combination method is proposed, which demonstrated high...
Electrical impedance tomography (EIT) is a newly developed technique by which impedance measurements from the surface of an object are reconstructed into impedance image. But in the initial stage, the EIT problem is regarded as the two-dimensional EIT problem, which ignores too much important information and makes it can't give the exact spatial information of the place where the impedance has changed...
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