Jason J. Ford, Timothy L. Molloy, Joanne L. Hall
This paper investigates compressed sensing using hidden Markov models (HMMs) and hence provides an extension of recent single frame, bounded error sparse decoding problems into a class of sparse estimation problems containing both temporal evolution and stochastic aspects. This paper presents two optimal estimators for compressed HMMs. The impact of measurement compression on HMM filtering […]
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Chang Won Lee, Jaepil Ko, Tae-Young Choe
Recursive Gaussian filters are more efficient than basic Gaussian filters when its filter window size is large. Since the computation of a point should start after the computation of its neighborhood points, recursive Gaussian filters are line oriented. Thus, the degree of parallelism is restricted by the length of the data image. In order to […]
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Linus Kallberg, Thomas Larsson
Minimum enclosing balls are used extensively to speed up multidimensional data processing in, e.g., machine learning, spatial databases, and computer graphics. We present a case study of several acceleration techniques that are applicable in enclosing ball algorithms based on repeated farthest-point queries. Parallel GPU solutions using CUDA are developed for both low- and high-dimensional cases. […]
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Maria G. Sanchez, Vicente Vidal, Josep Arnal, Anna Vidal
A parallel algorithm to remove impulsive noise in digital images using heterogeneous CPU/GPU computing is proposed. The parallel denoising algorithm is based on the peer group concept and uses an Euclidean metric. In order to identify the amount of pixels to be allocated in multi-core and GPUs, a performance analysis using large images is presented. […]
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H.K. Kim, H.J. Lee
A noise in digital image degrades the performance of image processing. These images are most often used in medical field for diagnosis and treatment. Thus, there is a huge demand for high quality images from the medical field. The current algorithms to process useable images are derived using Gaussian blur filter. However, using such isotropic […]
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Zhongya Wang, Ying Liu, Pengshan Ma
Collaborative filtering (CF) is one of the essential algorithms in recommendation system. Based on the performance analysis, two computational kernels are identified. In order to accelerate CF on large-scale data, a CUDA-enabled parallel CF approach is proposed where an efficient data partition scheme is proposed as well. Various optimization techniques are also applied to maximize […]
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Han Xiao, Yu-Pu Song, Qing-Lei Zhou
With the development of satellite remote sensing technology, satellite remote sensing data obtained by the amount will increase rapidly. Consequently, the process of Wallis transformation is faced with such challenges as large data size, high intensity, high computational complexity and large computational quantity, and so on. A fast algorithm and efficient implementation of Wallis filtering […]
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Aruna Dore, Sunitha Lasrado
The fundamental task required for any image or Video processing applications like video surveillance, medical imaging is Edge detection. Any of the filters available can be used to detect the edges. In this paper Sobel Edge filter is used for comparing the performance analysis on CPUs and GPUs and from this study it is found […]
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Salvatore Cuomo, Pasquale De Michele, Francesco Piccialli
Non-Local Means (NLM) algorithm is widely considered as a state-of-the-art denoising filter in many research fields. Its high computational complexity leads researchers to the development of parallel programming approaches and the use of massively parallel architectures such as the GPUs. In the recent years, the GPU devices had led to achieve reasonable running times by […]
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Anders Eklund, Paul Dufort
We have presented solutions for fast non-separable floating point convolution in 2, 3 and 4 dimensions, using the CUDA programming language. We believe that these implementations will serve as a complement to the NPP library, which currently only supports 2D filters and images stored as integers. The shared memory implementation with loop unrolling is approximately […]
Shruti S.Agrawal, C.K.Kurve
Digital Image Processing is an evergreen area of research in the signal processing domain. Denoising of digital images is one of the most fundamental operations that is performed in the pre-processing stage of almost all image processing operations. This important feature makes denoising as one of the lucrative research areas within the broad area of […]
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Jonas Adler
A GPU Monte Carlo code for x-ray photon transport has been implemented and extensively tested. The code is intended for scatter compensation of cone beam computed tomography images. The code was tested to agree with other well known codes within 5% for a set of simple scenarios. The scatter compensation was also tested using an […]
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