This note describes a non-rigid image registration approach that parametrizes the deformation field by an additive composition of a similarity transformation and a set of Gaussian radial basis functions. The bases'...
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ISBN:
(纸本)9780819494283
This note describes a non-rigid image registration approach that parametrizes the deformation field by an additive composition of a similarity transformation and a set of Gaussian radial basis functions. The bases' centers, variances, and weights are determined with a global optimization approach that is introduced in this work. This approach consists of simulated annealing with a particle filter based generator function to perform the optimization. Additionally, a local refinement is performed to capture the remaining misalignment. The deformation is constrained to be physically meaningful (i.e., invertible). Results on 2D and 3D data sets demonstrate the algorithm's robustness to large deformations.
How to design a low-cost, reliable and real-time target recognition system with large amount of data has become a hot topic in the area of imageprocessing. However, Edge detection has played an important role in targ...
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How to design a low-cost, reliable and real-time target recognition system with large amount of data has become a hot topic in the area of imageprocessing. However, Edge detection has played an important role in target recognition system. The threshold of traditional canny edge detection algorithm must be setting by human, and has a large number of calculations. In order to overcome the shortcomings of the traditional Canny algorithm, proposing an adaptive threshold edge detection algorithm, and realizing it by hardware. This paper will introduce the implementation of the common low-level imageprocessing algorithm in the FPGA, including color space convert module, edge extraction algorithms module, Hough transform module. The results of the experiment indicate that to realize the large amount of calculation of imageprocessing by FPGA hardware logic, not only improves the effect of imageprocessing, but also has high real-time!
This paper presents an analytical performance prediction model and methodology that can be used to predict the execution time, speedup, scalability and similar performance metrics of a targe set of imageprocessing op...
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This paper presents an analytical performance prediction model and methodology that can be used to predict the execution time, speedup, scalability and similar performance metrics of a targe set of imageprocessing operations running on a p-processor parallel system. The model which requires only a few parameters obtainable on a minimal system can help in the systematic design, evaluation and performance tuning of parallel imageprocessingsystems. Using the model one can reason about the performance of a parallel imageprocessing system prior to implementation. The method can also support programmers in detecting critical parts of an implementation and system designers in predicting hardware performance and the effect of hardware parameter changes on performance. The execution of parallel imageprocessing operations was studied and operations were arranged in three main problem classes based on data locality and the communication patterns of the algorithms. The core of the method is the derivation of the overhead function, as it is the overhead that determines the achievable speedup. The overheads were examined and modelled for each class. The use of the method is illustrated by four class-representative imageprocessingalgorithms: image-scalar addition, convolution, histogram calculation and the Fast Fourier Transform. The developed performance model has been validated on a 16-node parallel machine and it has been shown that the model is able to predict the parallel run-time and other performance metrics of parallel imageprocessing operations accurately.
Signal, image and Synthetic Aperture Radar imagery algorithms in recent time are used in a daily routine. Due to huge data and complexity, their processing is almost impossible in a real time. Often imageprocessing a...
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ISBN:
(纸本)9781538669792
Signal, image and Synthetic Aperture Radar imagery algorithms in recent time are used in a daily routine. Due to huge data and complexity, their processing is almost impossible in a real time. Often imageprocessingalgorithms are inherently parallel in nature, so they fit nicely into parallel architectures multicore Central processing Unit (CPU) and Graphics processing Unit GPUs. In this paper imageprocessingalgorithms were evaluated, which are capable to execute in parallel manner on several platforms CPU and GPU. All algorithms were tested in TensorFlow, which is a novel framework for deep learning, but also for imageprocessing. Relative speedups compared to CPU were given for all algorithms. TensorFlow GPU implementation can outperform multi-core CPUs for tested algorithms, obtained speedups range from 3.6 to 15 times.
Binary imageprocessing is a powerful tool in many image and video applications. A reconfigurable processor is presented for binary imageprocessing in this paper. The processor's architecture is a combination of ...
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Binary imageprocessing is a powerful tool in many image and video applications. A reconfigurable processor is presented for binary imageprocessing in this paper. The processor's architecture is a combination of a reconfigurable binary processing module, input and output image control units, and peripheral circuits. The reconfigurable binary processing module, which consists of mixed-grained reconfigurable binary compute units and output control logic, performs binary imageprocessing operations, especially mathematical morphology operations, and implements related algorithms more than 200 f/s for a 1024 x 1024 image. The periphery circuits control the whole imageprocessing and dynamic reconfiguration process. The processor is implemented on an EP2S180 field-programmable gate array. Synthesis results show that the presented processor can deliver 60.72GOPS and 23.72 GOPS/mm(2) at a 220-MHz system clock in the SMIC 0.18-mu m CMOS process. The simulation and experimental results demonstrate that the processor is suitable for real-time binary imageprocessing applications.
This paper first gives brief introduction to freeway Automatic Incident Detection (AID) algorithms on loop detector and it's existing problems, then proposes potential micro and macro freeway AID methods based on ...
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This paper first gives brief introduction to freeway Automatic Incident Detection (AID) algorithms on loop detector and it's existing problems, then proposes potential micro and macro freeway AID methods based on imageprocessing and tries to find how difficult the problems are, and finally, from imageprocessing viewpoint presents some possible solutions.
This paper describes the interpolation algorithm which contains shooting or ringing artifact suppression based on windowed sinc interpolator. In general, the windowed sinc interpolator can achieve better performance b...
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ISBN:
(纸本)9780819494283
This paper describes the interpolation algorithm which contains shooting or ringing artifact suppression based on windowed sinc interpolator. In general, the windowed sinc interpolator can achieve better performance by using wider window. However, using wide window causes more ripples that produce unwanted defects such as ringing or shooting artifact. Therefore, shooting reduction technique is proposed in this paper for using wider windows to improve the performance without shooting artifact. The proposed algorithm can suppress shooting artifact by using median sinc interpolator and it can be also used as a post processor for many kernel-based interpolation methods. The resulted image shows that the proposed algorithm can maintain local details and suppress shooting artifact in the image well.
The last few years have seen a massive increment in the use of the Internet as a channel for sharing and transmitting data, thus requiring the need for copyright protection schemes able to preserve the ownership of th...
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ISBN:
(纸本)9780819494283
The last few years have seen a massive increment in the use of the Internet as a channel for sharing and transmitting data, thus requiring the need for copyright protection schemes able to preserve the ownership of the data. The idea of embedding a watermark directly in the data is however unacceptable in various fields of application, due to the intrinsic degradation introduced by non reversible watermarking schemes. Hence some zero watermarking schemes have been developed. In this work we propose an optimization of a recent watermarking method based on visual cryptography, by improving results against most commont types of attacks and achieving a higher perceptual quality of the extracted mark.
Semifragile watermarking techniques aim to prevent tampering and fraudulent use of modified images. A semifragile watermark monitors the integrity of the content of the image but not its numerical representation. Ther...
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Semifragile watermarking techniques aim to prevent tampering and fraudulent use of modified images. A semifragile watermark monitors the integrity of the content of the image but not its numerical representation. Therefore, the watermark is designed so that the integrity is proven if the content of the image has not been tampered with, despite some mild processing on the image. However, if parts of the image are replaced with the wrong key or are heavily processed, the watermark information should indicate evidence of forgery. We compare the performance of eight semifragile watermarking algorithms in terms of their miss probability under forgery attack, and in terms of false alarm probability under nonmalicious signal processing operations that preserve the content and quality of the image. We propose desiderata for semifragile watermarking algorithms and indicate the promising algorithms among existing ones. (C) 2004 SPIE and IST.
A method that integrates tone mapping for high dynamic range (HDR) gray-scale images with JPEG compression is proposed. The tone mapping operator (TMO) is block-based, and structured so that the same discrete cosine t...
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ISBN:
(纸本)9780819494283
A method that integrates tone mapping for high dynamic range (HDR) gray-scale images with JPEG compression is proposed. The tone mapping operator (TMO) is block-based, and structured so that the same discrete cosine transform (DCT) that is used for the JPEG compression serves to complete a major part of the tone-mapping operation. Simulations have been done on high dynamic range images from the Debevec library. Experimental results show the technique successfully tone maps and compresses simultaneously;the number of bits per pixel is reduced from 32 to an average of 0.67 by the compression, with an average PSNR of 56.3 dB for the compressed tone-mapped images compared to images that have been only tone-mapped. The output of the proposed method is an image that requires only limited storage space, and can be decompressed with a standard JPEG decoder.
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