Segmentation and classification are important problems with applications in areas like textural analysis and pattern recognition. This paper describes a single-stage approach to solve the image segmentation/classifica...
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ISBN:
(纸本)0780362985
Segmentation and classification are important problems with applications in areas like textural analysis and pattern recognition. This paper describes a single-stage approach to solve the image segmentation/classification problem down to the pixel level, using energy density functions based on the wavelet transform. The energy density functions obtained, called Pseudo Power Signatures, are essentially functions of the scale and orientation, and are obtained using separable approximations to the 2-D wavelet transform. A significant advantage of these representations is that they are invariant to signal magnitude, and spatial location within the: object of interest. Further, they lend themselves to fast and simple classification routines. We provide a complete formulation of the signature determination problem for 2-D, and propose an effective, albeit simple, technique based on a tensor singular value analysis, to solve the problem. We also present an efficient computational algorithm, and a simulation result reflecting the strengths and limitations of this approach.
Typical neuroimaging studies place great emphasis on not only the estimation but also the standard error estimates of underlying parameters derived from a temporal model. This is principally done to facilitate the use...
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ISBN:
(纸本)0819450804
Typical neuroimaging studies place great emphasis on not only the estimation but also the standard error estimates of underlying parameters derived from a temporal model. This is principally done to facilitate the use of t-statistics. Due to the spatial correlations in the data, it can often be more advantageous to interrogate models in the wavelet domain than in the image domain. However, widespread acceptance of these wavelet techniques has been hampered due to the limited ability to generate both parametric and error estimates in the image domain from these temporal models in the wavelet domain, without which comparison to current standard non-wavelet methods can prove difficult.
The denoising of video data should take into account both temporal and spatial dimensions, however, true 3D transforms are rarely used for video denoising. Separable 3-D transforms have artifacts that degrade their pe...
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ISBN:
(纸本)0819450804
The denoising of video data should take into account both temporal and spatial dimensions, however, true 3D transforms are rarely used for video denoising. Separable 3-D transforms have artifacts that degrade their performance in applications. This paper describes the design and application of the non-separable oriented 3-D dual-tree wavelet transform for video denoising. This transform gives a motion-based multi-scale decomposition for video - it isolates in its subbands motion along different directions. In addition, we investigate the denoising of video using the 2-D and 3-D dual-tree oriented wavelet transforms, where the 2-D transform is applied to each frame individually.
Dual tree complex wavelet transform(DTCWT) is a form of discrete wavelet transform, which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts. The purposes o...
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ISBN:
(纸本)9780819489326
Dual tree complex wavelet transform(DTCWT) is a form of discrete wavelet transform, which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts. The purposes of de-noising are reducing noise level and improving signal to noise ratio (SNR) without distorting the signal or image. This paper proposes a method for removing white Gaussian noise from ECG signals and biomedical images. The discrete wavelet transform (DWT) is very valuable in a large scope of de-noising problems. However, it has limitations such as oscillations of the coefficients at a singularity, lack of directional selectivity in higher dimensions, aliasing and consequent shift variance. The complex wavelet transform CWT strategy that we focus on in this paper is Kingsbury's and Selesnick's dual tree CWT (DTCWT) which outperforms the critically decimated DWT in a range of applications, such as de-noising. Each complex wavelet is oriented along one of six possible directions, and the magnitude of each complex wavelet has a smooth bell-shape. In the final part of this paper, we present biomedical image and signal de-noising by the means of thresholding magnitude of the wavelet coefficients.
In this study, a new digital image watermarking algorithm based on moment-based image normalization and the two dimensional complex wavelet transform (2D-CWT) was developed. Normalization provides robustness against g...
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ISBN:
(纸本)9781424419982
In this study, a new digital image watermarking algorithm based on moment-based image normalization and the two dimensional complex wavelet transform (2D-CWT) was developed. Normalization provides robustness against geometrical distortions, while the 2D-CWT increases robustness for attacks such as noise, linear and nonlinear filtering, JPEG compression. That added watermark satisfies both transparency and robustness requirements was achieved by taking the properties of the human visual system account.
This paper considers the extraction of information from a locally stationary process modelled by wavelet packets. A method is presented to select subprocesses that characterize the key aspects of the nonstationary pro...
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ISBN:
(纸本)0819450804
This paper considers the extraction of information from a locally stationary process modelled by wavelet packets. A method is presented to select subprocesses that characterize the key aspects of the nonstationary process for pattern analysis. The estimated parameters of the selected subprocesses are used to infer the process' time varying behavior. The estimated parameters can be used as features in the attempt to distinguish changing states within a process or differentiate two different locally stationary processes.
In this paper, an embedded DCT-based image coding algorithm is described. The decoder can cut the bitstream at any point and therefore reconstruct an image at lower rate. The quality of the reconstructed image at this...
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ISBN:
(纸本)0780344286
In this paper, an embedded DCT-based image coding algorithm is described. The decoder can cut the bitstream at any point and therefore reconstruct an image at lower rate. The quality of the reconstructed image at this lower rate would be the same as if the image was coded directly at that rare. The algorithm outperforms any other DCT-based coders published in the literature, including the JPEG algorithm. Moreover, our DCT-based embedded image coder gives results close to the best wavelet-based coders. The algorithm is very useful in various applications, like WWW, fast browsing of databases, etc.
In this paper we give a brief introduction to filter banks over commutative rings. In contrast to filter banks over the real numbers, we employ finite ring arithmetic to control the number of bits in the signal repres...
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ISBN:
(纸本)0819425915
In this paper we give a brief introduction to filter banks over commutative rings. In contrast to filter banks over the real numbers, we employ finite ring arithmetic to control the number of bits in the signal representations. This way we avoid the coefficient swell problem that is preeminent in rings of characteristic zero. We derive decompositions for images that are tailored to dedicated hardware implementations. These decompositions reduce the size of line-buffers which dominate the silicon area in integrated circuit implementations. As an application, we derive a lossless compression scheme for 8 bit monochrome images using wavelet filters with values in the ring Z/256Z.
In optical phase shift profilometry, parallel fringe patterns are projected onto an object and the deformed fringes are captured using a digital camera. It is of particular interest because it enables reconstruction o...
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ISBN:
(纸本)9781424479948
In optical phase shift profilometry, parallel fringe patterns are projected onto an object and the deformed fringes are captured using a digital camera. It is of particular interest because it enables reconstruction of the 3D shape of the object using just a few image captures, which facilitates real time applications. However, when using the approach in real life environment, it is noticed that the noise in the captured images can greatly affect the reconstruction quality. In this paper, we firstly analyze why the noisy fringe images can best be analyzed using the oriented 2D dual tree complex wavelet transform. We then suggest an effective yet simple method for enhancing the noisy fringe images. Both the simulation and experiment results show that the new approach can give good performance in reconstruction with fringe images even at high noise level.
This paper describes the current status of our program of work in the area of digital image enhancement using wavelet-based multi-scale processing. We are developing an all-waveletimageprocessing algorithm to enhanc...
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ISBN:
(纸本)085296692X
This paper describes the current status of our program of work in the area of digital image enhancement using wavelet-based multi-scale processing. We are developing an all-waveletimageprocessing algorithm to enhance the quality of direct digital thorax images, by the manipulation of the data within scale-specific sub-bands. This method avoids the presentation compromises which may result from the global application of unsharp mask based image enhancement methods which are commonly used in medical imaging. This is achieved by applying specific processing to image components according to their scale. In particular contrast enhancement, de-noising and sharpening stages are all tailored to the noise and feature characteristics of Thoravision digital chest X-ray images. Whilst our experiments to date convince us that processing digital X-ray images within the wavelet domain is a useful tool for improving diagnostic image quality, our concerns now focus on the subtlety of this processing, since it can be prone to artefact generation if applied incorrectly. We are also interested in optimising the way in which wavelet based image enhancement must be presented to our clinical colleagues to meet their diagnostic needs.
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