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While GPGPU programming offers faster computation of highly parallelized code, the memory bandwidth between the system and the GPU can create a bottleneck that reduces the potential gains. CUDA is a prominent GPGPU API which can transfer data to and from system code, and which can also access data used by 3D rendering APIs. In an application that relies on both GPU programming APIs to accelerate 3D...
Graphic Processing Unit (GPU) has involved into a parallel computation for it's massively multi threaded architecture. Due to its high computational power, GPU has been used to deal with many problems that can be easily parallelized. This paper will present a GPU based spot noise parallel algorithm for 2D vector field visualization. It uses spot noise method with GPU resources and compute unified...
The retinex algorithm is commonly used to image enhancement. Recently, the image size what we usually use, is bigger and bigger. The digital camera use big size images and the television is change to HD television. So the image enhancement time is longer and longer and it needs more powerful system such as multi-core, many-core systems. But these multi-core, many-core systems or powerful systems are...
Motion estimation(ME) is one of the most important modules in digital video encoding/decoding and video post processing. High-quality and fast ME algorithms are desired by many applications. In this paper, motion estimation algorithms are explored in terms of execution efficiency on the CUDA (Compute Unified Device Architecture) technology which is a parallel computing architecture developed by nVIDIA...
This paper shows approaches to accelerate pixel-level image fusion speed using graphics hardware. Recently, to improve visibility through maximization of information collected through development of various sensors and improvement of sensing technology, the importance of not only development of new fusion algorithm but speed of fusion process is increasing. Though specialized fusion boards for real...
Recent advancements in semi-conductor fabrication has led to a dramatic increase in the size of data sets of advanced imaging sensors. While increased pixel counts leads to greater area coverage and higher resolution, it also results in higher image processing time. If real-time image processing is required, power and size requirements go up as large data processing computers are required to keep...
A Graphics Processing Unit (GPU) based measuring system which is used for processing images from a camera to provide information about displacement is presented in this work. The proposed approach has been developed for measuring small movements of micro robotic systems based on synthetic IPMC (Ionic Polymer Metal Composites) materials using CUDA (Compute Unified Device Architecture) technology. The...
This paper presents an efficient real-time implementation of an unsupervised textile fabric defect detection algorithm called ITT using the concept of iterative tensor tracking on graphics processing unit (GPU). The algorithm adopts a new local image descriptor, Spatial Histograms of Oriented Gradients (S-HOG), which is shift-invariant, light insensitive and space scalable. For a given textile fabric...
We investigate a fast pedestrian localization framework that integrates the cascade-of-rejectors approach with the Histograms of Oriented Gradients (HoG) features on a data parallel architecture. The salient features of humans are captured by HoG blocks of variable sizes and locations which are chosen by the AdaBoost algorithm from a large set of possible blocks. We use the integral image representation...
With their parallel multi-core architecture, Programmable Graphics Processing Units (GPUs) are well suited for implementing biologically-inspired visual processing algorithms, such as Gabor filtering. We compare several GPU implementations of Gabor filtering. On the same graphics card (an NVIDIA GeForce 9800 GTX+) and for convolution kernel radii from 8 to 48 pixels, an algorithm that decomposes Gabor...
Motion estimation is an essential part in many video processing systems. The 3D recursive search block matching is the first affordable motion estimator at the consumer level and has already been used in many CE devices. This paper reveals the realization of this recursive algorithm on a graphics processing unit with a parallel architecture.
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