Discrete wavelet Transform (DWT) is widely used in signalprocessingapplications. In this paper, we describe hardware implementation of a lifting-based DWT, which is used in image compression. The CDF(2,2) lifting-ba...
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ISBN:
(纸本)9780819489326
Discrete wavelet Transform (DWT) is widely used in signalprocessingapplications. In this paper, we describe hardware implementation of a lifting-based DWT, which is used in image compression. The CDF(2,2) lifting-based wavelet transform is modeled and simulated using MATLAB. Based on DSP methodologies, the signal flow graph and dependence graph are derived. The dependence graph is optimized and used to implement the hardware description of the circuit in Verilog. We have synthesized and implemented the circuit using both Field Programmable Gate Array (FPGA) and Application Specific Integrated Circuit (ASIC) design approaches. To confirm the circuit operation, post-synthesis and post-layout simulations were done for FPGA and ASIC designs, respectively.
wavelet based compression schemes belong to the general class of transform coding schemes. We show how the genetic programming approach can be used to optimize such a compression scheme in the sense of rate-distortion...
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ISBN:
(纸本)0819419281
wavelet based compression schemes belong to the general class of transform coding schemes. We show how the genetic programming approach can be used to optimize such a compression scheme in the sense of rate-distortion. The results of optimized wavelet based compression scheme are compared with the JPEG compression standard. A prototype implementation of the method is realized as a distributed, parallel implementation on a heterogeneous Unix network.
This paper presents a completely blind or no-reference metric for estimation of perceived noise in images. This novel metric dubbed CINEMA (Content Independent Noise Estimation forMultimedia applications) is completel...
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This paper presents a completely blind or no-reference metric for estimation of perceived noise in images. This novel metric dubbed CINEMA (Content Independent Noise Estimation forMultimedia applications) is completely content unaware and aligns well with human perception. An HOG-based model is employed for selection of weak textured patches and a wavelet decomposition strategy is used for detecting and quantifying noise. Experimental results on the LIVE database show that CINEMA achieves consistently good performance for different noise levels as compared to many of the existing Full Reference and No Reference image Quality Assessment (IQA) metrics. We further show how CINEMA can be used to obtain an estimate ((sigma) over cap) of the noise standard deviation (sigma) with high accuracy. A MATLAB implementation of the model is available at https://***/site/blindiqa/cinema. (C) 2015 Published by Elsevier B.V.
The introduction of wavelets in signal and imageprocessing has provided a new tool to create innovative and novel methods for solving problems in the areas of data compression, signal analysis, and noise removal, to ...
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ISBN:
(纸本)081942840X
The introduction of wavelets in signal and imageprocessing has provided a new tool to create innovative and novel methods for solving problems in the areas of data compression, signal analysis, and noise removal, to name a few. Although wavelets are popular and used extensively in research and in engineering applications, their use in signature detection and classification is still an area open to extensive investigation. This paper discusses waveletimageprocessing working in synergy with other processing techniques to detect and recognize abnormal and cueing signatures that are important to diagnostic medicine - detection and recognition of microcalcification clusters in mammograms. In this application, an innovative detection algorithm that takes advantage of wavelet multiresolution analysis and synthesis is developed to assist radiologists looking for clusters of microcalcifications in digitized mammograms. Microcalcification regions may not be detectable by visual inspection or other detection techniques because of their inherent complexity. The algorithm presented in this paper successfully unmasks the complexity and limits the false positives. A thorough analysis, algorithm description and examples are shown in this paper.
In order to enhance the speed of imageprocessing we apply the optical wavelet transform to vision system by the method of photoelectric hybrid implementation. The state-of-the-art liquid crystal on silicon (LCoS) tec...
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ISBN:
(纸本)0819451541
In order to enhance the speed of imageprocessing we apply the optical wavelet transform to vision system by the method of photoelectric hybrid implementation. The state-of-the-art liquid crystal on silicon (LCoS) technology is applied to improve the signal-to-noise ratio of the wavelet transform. A fan out grating implemented by a phase-only LCoS is used to implement multiple channel optical processing. Therefore the parallelism of the vision system is improved further. The research results shows that the optical wavelet transform based vision system is reasonable and feasible. The image feature extraction by optical information processing can enhance the speed of vision processing.
This paper proposes a method which utilizes invariant wavelet features for correcting total occlusion in video surveillance applications. The proposed method extracts invariant wavelet features from the pre-occlusion ...
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ISBN:
(纸本)9781424414369
This paper proposes a method which utilizes invariant wavelet features for correcting total occlusion in video surveillance applications. The proposed method extracts invariant wavelet features from the pre-occlusion spatial image of disappearing objects. When new objects are detected during occlusion, their extracted invariant wavelet features are compared to those of lost objects to check for reappearance. When reappearance occurs, the proposed method rebuilds the correct correspondence map between pre-occlusion and post occlusion objects to continue to track the ones that were lost during total occlusion. Our results show that the proposed method is more robust than referenced methods especially when objects change or reverse their motion direction during occlusion.
This paper proposes a method for extracting subimages from a huge reference image by using lifting wavelet transforms that map integers to integers. Our integer-type lifting wavelet transform contains controllable fre...
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ISBN:
(纸本)0780362985
This paper proposes a method for extracting subimages from a huge reference image by using lifting wavelet transforms that map integers to integers. Our integer-type lifting wavelet transform contains controllable free parameters, which are constructed based on an integer version of Haar transform. Our learning method is to determine such free parameters using some subimages so as to vanish their high frequency components in the y- and x-directions. The learnt wavelet transform has the feature of the subimages. We apply such a wavelet transform to high frequency components of a reference image and check whether they are vanished of not, to detect a target subimage.
In this paper, we propose a new decomposition scheme for spatially adaptive wavelet packets. Contrary to the double tree algorithm, our method is non-uniform and shift-invariant in the time and frequency domains, and ...
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ISBN:
(纸本)0819437646
In this paper, we propose a new decomposition scheme for spatially adaptive wavelet packets. Contrary to the double tree algorithm, our method is non-uniform and shift-invariant in the time and frequency domains, and is minimal for an information cost function. We propose some restrictions to our algorithm to reduce the complexity and permitting us to provide some time-frequency partitions of the signal in agreement with its structure. This new "totally" non-uniform transform, more adapted than Malvar, Packets or dyadic double-tree decomposition, allows the study of all possible time-frequency partitions with the only restriction that the blocks are rectangular. It permits one to obtain a satisfying Time-Frequency representation, and is applied for the study of EEG signals.
In this paper, we describe about a triangular lattice structuring method for 3-D polygonal mesh data and a shape-adaptive wavelet transform of the structured geometry and textural data. Efficient representations of a ...
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ISBN:
(纸本)0780376226
In this paper, we describe about a triangular lattice structuring method for 3-D polygonal mesh data and a shape-adaptive wavelet transform of the structured geometry and textural data. Efficient representations of a 3-D object data has attracted wide attention for transmission and storage of computer graphics data and interactive design in manufacturing. Polygonal mesh data, which consist of connectivity information, geometry data and textural data, are often used for representing a 3-D object in many applications. We propose a method for structuring the polygonal mesh data on a triangular lattice plane with expanded nodes. And a shape-adaptive wavelet coding method is applied to the structured geometry data considering the expanded nodes. Experimental results show that the proposed method gives better coding performance than the Topologically Assisted Geometry Compression scheme.
A new scheme to search perceptually significant wavelet coefficients for effective digital watermark casting is proposed in this research, An adaptive method is developed to determine significant subbands and select a...
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ISBN:
(纸本)0819429155
A new scheme to search perceptually significant wavelet coefficients for effective digital watermark casting is proposed in this research, An adaptive method is developed to determine significant subbands and select a number of significant coefficients in these subbands. Experimental results show that the cast watermark can be successfully retrieved after various attacks including signalprocessing, geometric processing, noise adding, JPEG and wavelet-based compression methods.
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