FPGA components are widely used today to perform various algorithms (digital filtering) in real time. The emergence of Dynamically Reconfigurable (DR) FPGAs made it possible to reduce the number of necessary resources...
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ISBN:
(纸本)0819441880
FPGA components are widely used today to perform various algorithms (digital filtering) in real time. The emergence of Dynamically Reconfigurable (DR) FPGAs made it possible to reduce the number of necessary resources to carry out an imageprocessing application (tasks chain). We present in this article an imageprocessing application (image rotation) that exploits the FPGA's dynamic reconfiguration feature. A comparison is undertaken between the dynamic and static reconfiguration by using two criteria, cost and performance criteria. For the sake of testing the validity of our approach in terms of Algorithm and Architecture Adequacy, we realized an AT40K40 based board ARDOISE.
The goal of this project is to improve the performance of the parallel computer SYMPATI2. This SIMD processor based system performs with a good efficiency the low level imageprocessing operations, but this efficiency...
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The goal of this project is to improve the performance of the parallel computer SYMPATI2. This SIMD processor based system performs with a good efficiency the low level imageprocessing operations, but this efficiency is drastically cut when handling an intermediate level class of algorithms. This study emphasis the drawbacks encountered to perform such operations. The main one is the interconnection between processors. So, a new interconnection network, called the open intelligent network, is proposed and added to SYMPATI2 to form SYMPATIX. This network detailed below allows irregular transfers of data between the different processing elements of the new system. Furthermore, this network allows the efficient interconnection of specific modules. In this paper, the architecture is evaluated on representative algorithms of imageprocessing. Then, a behavioural model of SYMPATIX is described using a hardware description language, the VHDL. Our SIMD computer efficiency has been considerably upgraded for the low and intermediate levels of imageprocessing. Furthermore, its application area was extended. The last part of the paper describes the performance obtained with simulations.
image reconstruction algorithms for computerized tomography are of interest for both medical and industrial applications. The special geometry of these image reconstruction applications can be used to implement optima...
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image reconstruction algorithms for computerized tomography are of interest for both medical and industrial applications. The special geometry of these image reconstruction applications can be used to implement optimal reconstruction algorithms, such as the minimum variance estimator, in a computationally efficient manner which could become competitive with popular approximate algorithms. As a result of measurement acquisition procedures of typical CT configurations, both fan-beam and parallel-beam arrangements lead to circulant matrix forms which can be used as the basis for fast algorithms. The general minimum variance estimator for this application is reviewed, and a fast algorithm is presented which uses Fourier Transform techniques.
Still-imageprocessingalgorithms are tailored to and depend crucially upon the properties of the class of images to which they are applied, for instance natural images in consumer digital cameras, medical images in f...
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ISBN:
(纸本)9781424456536
Still-imageprocessingalgorithms are tailored to and depend crucially upon the properties of the class of images to which they are applied, for instance natural images in consumer digital cameras, medical images in fMRI machines, and binary text images in some photocopiers. We describe a new and possibly very important class of images and tasks for which traditional algorithms seem ill-suited, and for which new algorithms and general methods and concepts are required. This new class of images arises in imaging systems designed through new, joint optimization methods where the optics and the imageprocessing are designed simultaneously in order to yield a high-quality digital image. These new design methods yield intermediate optical images that have unusual spatial, noise and chromatic properties ill-served by traditional image methods. Moreover, these new images present a number of novel challenges in imageprocessing hardware implementations such as constrained space-variance. We describe these briefly new, joint methods for designing digital-optical imaging systems, characterize the intermediate optical images they yield, and some of the digital imageprocessing challenges for producing high-quality still images from these sensed optical images.
A novel high- speed image super-resolution algorithm based on sparse representation for MEMS defect detection is proposed in this paper. Traditional super-resolution algorithms adopt a single dictionary to represent i...
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An approach to very rapid and real-time ellipse detection is described, Based on a modified RANSAC (RANdom Sample Consensus), and considering the parallel processing capabilities of a programmable graphics processing ...
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The statistic information of connected components are fundamental for imageprocessing, which could be acquired through connected components labeling. This paper proposes a hardware-efficient method for extracting sta...
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The statistic information of connected components are fundamental for imageprocessing, which could be acquired through connected components labeling. This paper proposes a hardware-efficient method for extracting statistic information of connected components in a binary image to accelerate imageprocessing in embedded application. The proposed method scans two adjacent rows with 2 x 2 template simultaneously, meanwhile, statistic information of runs are recorded. After scanning two rows, the equivalent runs are merged, and then statistic information of completed connected region is exported directly. This method scans an image only once, which could reduce off-chip memory access massively. For a determined image resolution, the requirement of on-chip memory resource is also confirmed and not affected by the number of connected components. This algorithm is modeled with Verilog, and the simulation result shows that average processing speed could be real-time for various images with different resolution. Furthermore, the memory cost is little compared to other hardware based algorithms for labeling connected components, and the proposed method is appropriated for hardware implementation.
Next generations of image and video coding methods should of course be efficient in terms of compression, but also propose advanced functionalities. Among these functionalities such as scalability, lossy and lossless ...
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ISBN:
(纸本)9780819494283
Next generations of image and video coding methods should of course be efficient in terms of compression, but also propose advanced functionalities. Among these functionalities such as scalability, lossy and lossless coding, data protection, Rate Distortion Optimization (RDO) and Rate Control (RC) are key issues. RDO aims at optimizing compression performances, while RC mechanism enables to exactly compress at a given rate. A less common functionality than RC, but certainly more helpful, is Quality Control (QC): the constraint is here given by the quality. In this paper, we introduce a joint solution for RDO and QC applied to a still image codec called Locally Adaptive Resolution (LAR), providing scalability both in resolution and SNR and based on a multi-resolution structure. The technique does not require any additional encoding pass. It relies on a modeling and estimation of the prediction errors obtained in an early work. First, quality constraint is applied and propagated through the whole resolution levels called pyramid. Then, the quantization parameters are deduced considering inter and intra pyramid level relationships. Results show that performances of the proposed method are very close to an exhaustive search solution.
Person re-identification through a camera network deals with finding a correct link between consecutive observations of the same target among different cameras in order to choose the most probable correspondence among...
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ISBN:
(纸本)9780819494283
Person re-identification through a camera network deals with finding a correct link between consecutive observations of the same target among different cameras in order to choose the most probable correspondence among a set of possible matches. This task is particularly challenging in presence of low-resolution camera networks. In this work, a method for people re-identification in a framework of low-resolution camera network is presented. The proposed approach can be divided in two parts. First, the illumination changes of a target while crossing the network is analyzed. The color structure is evaluated using a novel color descriptor, the Color Structure Descriptor, which describes the differences of dominant colors between two regions of interest. Afterwards, a new pruning system for the links, the Target Color Structure is proposed. Results shows that the improvements achieved applying Target Color Structure control are up to 4% for the top rank and up to 16% considering the first eleven more similar candidates.
As a cross task of natural language processing and computer vision, image captioning is a key technology to explore the transformation of artificial intelligence visual perception to high-level semantic understanding....
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