We present a novel method to extract subimages from a huge reference image by using integer-type lifting wavelet transforms. Our integer to integer lifting wavelet transform contains controllable free parameters in th...
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ISBN:
(纸本)0819437646
We present a novel method to extract subimages from a huge reference image by using integer-type lifting wavelet transforms. Our integer to integer lifting wavelet transform contains controllable free parameters in the lifting term, which is constructed based on an integer version of Haar wavelet transform. Such free parameters are trained following a vanishing criterion for low frequency components of query images. The trained parameters have characteristics of the query images. We apply a lifting wavelet transform with such parameters to a reference image and check whether they satisfy our vanishing criterion or not, to extract target subimages.
Within the multi-resolution analysis, the study of the image compression algorithm using the Haar wavelet has been performed. We have studied the dependence of the image quality on the compression ratio. Also, the var...
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ISBN:
(数字)9781510603349
ISBN:
(纸本)9781510603332;9781510603349
Within the multi-resolution analysis, the study of the image compression algorithm using the Haar wavelet has been performed. We have studied the dependence of the image quality on the compression ratio. Also, the variation of the compression level of the studied image has been obtained. It is shown that the compression ratio in the range of 8-10 is optimal for environmental monitoring. Under these conditions the compression level is in the range of 1.7 - 4.2, depending on the type of images. It is shown that the algorithm used is more convenient and has more advantages than Winrar. The Haar wavelet algorithm has improved the method of signal and imageprocessing.
A new approach to FPGA implementation of two-dimensional discrete wavelet transform is presented. This architecture allow high accurate and sampling rate DWT realization based on FIR filters of substantial length to b...
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ISBN:
(纸本)0819425915
A new approach to FPGA implementation of two-dimensional discrete wavelet transform is presented. This architecture allow high accurate and sampling rate DWT realization based on FIR filters of substantial length to be implemented on current generation FPGAs. The scheme is based on two parallel pipelined linear phase 17-tap FIR filters with common shift register, partial adders and look-up tables as coefficient multipliers with 4-stage pipelined architecture. The transform is realized in three stages controlled by the state machine, where temporary (L and H) and final subimages (LL, LH, HL, and HH) are created. High throughput (1050 MIPS) and external memory controller allow efficient concurrent cooperation with external processors.
A new efficient image coding scheme, based on Quadtree Representation and Block Entropy Coding (QRBEC), for encoding the wavelet transform coefficients of images is presented. The property of HVS is also incorporated ...
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ISBN:
(纸本)0818679204
A new efficient image coding scheme, based on Quadtree Representation and Block Entropy Coding (QRBEC), for encoding the wavelet transform coefficients of images is presented. The property of HVS is also incorporated into the quantization process. In addition, how to flexibly control the quantization level as well as output bitrate of the coder is also investigated. The coding efficiency of the coder is quite competitive with the well-known EZW coder, and requires less computation burden. The proposed coding scheme can also be applied in image sequence coding, resulting in satisfactory performance.
signal decomposition techniques are an important tool for analyzing nonstationary signals. The proper selection of time-frequency basis functions for the decomposition is essential to a variety of signalprocessing ap...
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ISBN:
(纸本)0819418447
signal decomposition techniques are an important tool for analyzing nonstationary signals. The proper selection of time-frequency basis functions for the decomposition is essential to a variety of signalprocessingapplications. The discrete wavelet transform (DWT) is increasingly being used for signal analysis, but not until recently has attention been paid to the time-frequency resolution property of wavelets. This paper describes additional results on our procedure to design wavelets with better time-frequency resolution. In particular, our optimal duration-bandwidth product wavelets (ODBW) have better duration-bandwidth product, as a function of wavelet-defining filter length N, than Daubechies' minimum phase and least- asymmetric wavelets, and Dorize and Villemoes' optimum wavelets over the range N equals 8 to 64. Some examples and comparisons with these traditional wavelets are presented.
In this paper we investigate the benefits of using local wavelet analysis to the face recognition problem. We examine two possible approaches to perform local wavelet analysis. In the first approach, discrete wavelet ...
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ISBN:
(纸本)9781424407194
In this paper we investigate the benefits of using local wavelet analysis to the face recognition problem. We examine two possible approaches to perform local wavelet analysis. In the first approach, discrete wavelet transform is performed on the entire face image and then the transformed image is partitioned into non-overlapping rectangular blocks. In the second approach, as in the JPEG2000 standard, the input face image is first partitioned into non-overlapping rectangular blocks, and then on each block discrete wavelet transformation is performed. Proposed approaches are tested against the occlusion problem using the AR face database and significant improvements are observed in the face recognition performance.
The discrete wavelet transform was introduced as a linear operator. It works on signals that are modeled as functions from the integers into the real or complex numbers. Since many signals have finite function values,...
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ISBN:
(纸本)0819441929
The discrete wavelet transform was introduced as a linear operator. It works on signals that are modeled as functions from the integers into the real or complex numbers. Since many signals have finite function values, a linear discrete wavelet transform over a finite ring has been proposed recently. Another recent development is the research of nonlinear wavelet transforms triggered by the introduction of Sweldens' lifting scheme. This paper builds on these developments and defines an essentially nonlinear translation invariant discrete wavelet transform that works on signals that are functions from the integers into any finite set. As only discrete arithmetic is needed, such transforms can be calculated very time efficiently. The basic properties of these generalized discrete wavelet transforms are given along with explicit examples.
Sleep Apnoea Syndromes (SAS) is a sleep disorder which caused breathing pauses during sleep at night. There is various method of analyzing sleep EEG signals can be found in the literature. In this paper both linear;Di...
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ISBN:
(纸本)9781509055593
Sleep Apnoea Syndromes (SAS) is a sleep disorder which caused breathing pauses during sleep at night. There is various method of analyzing sleep EEG signals can be found in the literature. In this paper both linear;Discrete wavelet Transform (DWT) and non-linear;Approximate Entropy (ApEn) extraction methods were performed to differentiate features of each sleep stages between apnoea and healthy person. The efficiency of both extraction methods was compared by using ANOVA. In our study, we observed the non-linear feature of ApEn improves the ability to discriminate healthy and sleep apnoea at different sleep stages.
We introduce a general framework for computing the continuous wavelet transform (CWT). Included in this framework is an FFT implementation as well as fast algorithms which achieve O(1) complexity per wavelet coefficie...
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ISBN:
(纸本)0819422134
We introduce a general framework for computing the continuous wavelet transform (CWT). Included in this framework is an FFT implementation as well as fast algorithms which achieve O(1) complexity per wavelet coefficient. The general approach that we present allows a straight forward comparison among a large variety of implementations. In our framework, computation of the CWT is viewed as convolving the input signal with wavelet templates that are the oblique projection of the ideal wavelets into one subspace orthogonal to a second subspace. We present this idea and discuss and compare particular implementations.
We present examples of a new type of wavelet basis functions that are orthogonal across shifts, but not across scales. The analysis functions are low order splines while the synthesis functions are polynomial splines ...
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ISBN:
(纸本)0819422134
We present examples of a new type of wavelet basis functions that are orthogonal across shifts, but not across scales. The analysis functions are low order splines while the synthesis functions are polynomial splines of higher degree n2. The approximation power of these representations is essentially as good as that of the corresponding Battle- Lemarie orthogonal wavelet transform, with the difference that the present wavelet synthesis filters have a much faster decay. This last property, together with the fact that these transformation s are almost orthogonal, may be useful for image coding and data compression.
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