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Kernel density estimation is a popular method for identifying crime hotspots for the purpose of data-driven policing. However, computing a kernel density estimate is computationally intensive for large crime datasets, and the quality of the resulting estimate depends heavily on parameters that are difficult to set manually. Inspired by methods from image processing, we propose a novel way for performing...
Rich information could be extracted from the high dimensional light field (LF) data, and one of the most fundamental output is scene depth. State-of-the-art depth calculation methods produce noisy calculations especially over texture-less regions. Based on Super-pixel segmentation, we propose to incorporate multi-level disparity information into a Bayesian Particle Filtering framework. Each pixels'...
Model reduction by moment matching does not preserve, in a systematic way, the transient response of the system to be reduced, thus limiting the use of this model reduction technique in control problems. With the final goal of designing reduced-order models which can effectively be used (not just for analysis but also) for control purposes, we determine, using a data-driven approach, an estimate of...
For the seawater background interference problem in ship detection of high resolution remote sensing images, the characteristics of seawater background are analyzed deeply in this paper. And it's found that there is consistent in local but continuous variation in large range. On the basis of above analysis, a Gauss variable surface seawater background model for high resolution remote sensing images...
Most Traditional algorithms using only unilateral estimation or bidirectional estimation usually produce poor visual quality because of the fact that the unilateral motion estimation suffers from holes and overlaps and the bidirectional motion estimation suffers from inaccurate motion vector. This paper presents a new improved Frame rate up conversion(FRUC) scheme which combines the unilateral estimation...
Dermoscopy images usually suffer from spatially-varying defocus blur, which will easily influence the lesion analysis result and lead to wrong aided diagnosis. In this paper, a novel blind deblurring framework is proposed for dermoscopy images with spatially-varying defocus blur. The defocus map is firstly estimated by support vector regressor (SVR) learning model using the natural scene statistics...
This paper proposes a new signal-to-noise ratio (SNR) estimation technique on scanning electron microscope (SEM) image, using linear regression. The method is based on the single image approach. Four good quality images are used to compare the proposed method and the existing methods: nearest neighborhood, first order interpolation and piecewise cubic Hermite interpolation. The results are compared...
Fine frequency estimation of a single complex sinusoid is considered. We propose to refine the frequency estimation provided by the state-of-the-art methods based on three discrete Fourier transform (DFT) samples around the DFT maximum. To that end, parabolic interpolation of the periodogram peak is used. With the calculation of only three additional periodogram samples, the Cramér-Rao lower bound...
High resolution depth-maps, obtained by upsampling sparse range data from a 3D-LIDAR, find applications in many fields ranging from sensory perception to semantic segmentation and object detection. Upsampling is often based on combining data from a monocular camera to compensate the low-resolution of a LIDAR. This paper, on the other hand, introduces a novel framework to obtain dense depth-map solely...
The moving blocker method is economic and effective for scatter correction (SC) of cone-beam computed tomography (CBCT). However, at the regions with large intensity transition in the projection images in the axial blocker moving direction, the estimation of scatter signal from blocked regions in a single projection view can produce large errors, which can cause significant artifacts in reconstructed...
For the Sinusoid Signals with additive Gauss white noise, a frequency estimation algorithm based on discrete Fourier transform (DFT) interpolation algorithm is proposed in this paper. Based on the classical interpolation algorithm, the algorithm of this paper takes full use of the Peak Spectral Frequency and its neighbor spectral lines to estimate the frequency of the signal. The analysis and simulation...
It is a pervasive problem to accurately estimate the frequency of sinusoids contaminated by random noise, which has existed in many signal processing areas, including the application in mechanical fault diagnosis and prognostics. The interpolation discrete Fourier transform (DFT) method, employed in frequency domain, is one of the most well studied frequency estimation methods. In this paper, a comparison...
We consider the estimation of a n-dimensional vector x from the knowledge of noisy and possibility non-linear element-wise measurements of xxT, a very generic problem that contains, e.g. stochastic 2-block model, submatrix localization or the spike perturbation of random matrices. Using an interpolation method proposed by Guerra [1] and later refined by Korada and Macris [2], we prove that the Bethe...
Location based service relies on precise outdoor and indoor positioning technologies. Intuitively, indoor positioning is more difficult than outdoor positioning because of complicated environment. Fingerprint is a technique proposed to sketch the characteristic of every indoor location by adopting time-consuming measurements in offline phase. To minimize overhead, virtual fingerprint construction...
Phasor measurement units (PMUs) synchronize the measurements of current and voltage phasors in real time. This paper introduces a PMU simulation model for phasor estimation which uses a nonrecursive Discrete Fourier Transform (DFT) algorithm with linear interpolation. The algorithm was implemented and tested in the Real-Time Digital Simulator (RTDS). The algorithm is evaluated using the test signals...
Visible light communication (VLC) has been a research hotspot for broad bandwidth, high speed, and anti-interference. Power line communication (PLC) has the advantages of low cost and flexible access, which is connected and combined with VLC to be a hybrid communication system. We set up a communication system model of PLC&VLC based on orthogonal frequency division multiplexing (OFDM) modulation,...
In this paper, we study the performances of cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) and universal filtered orthogonal frequency division multiplexing (UF-OFDM) in the presence of phase noises. A phase noise mitigation scheme was proposed for CP-OFDM in a previous work. In this work, we extend the scheme to UF-OFDM. Phase noise estimation parameters are studied extensively...
Multispectral demosaicking, which is an extension of color demosaicking, is a challenging problem because each band is significantly undersampled and thus precise reconstruction is needed for the restoration of high-frequency components, such as edges, textures etc. In general, existing algorithms borrow high-frequency information either from different bands via inter-color correlation or from within...
Image upsampling from one input image gathers considerable attention in the field of computer vision. The problem is ill-posed because the number of known low-resolution (LR) pixels is less than that of unknown high-resolution (HR) pixels. Therefore, quality of an upsampled image depends on prior assumptions. Image interpolation methods are one of the image upsampling technologies and are faster than...
Non-Bayer color filter array (CFA) sensors have recently drawn attention due to their superior compression of spectral energy, ability to deliver improved signal-to-noise ratio, or ability to provide high dynamic range (HDR) imaging. Demosaicking methods that perform color interpolation of Bayer CFA data have been widely investigated. However, a bottleneck to the adaption of emerging non-Bayer CFA...
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