Considering the forthcoming spaceborne imaging instruments, on-board image compression is now essential due to the limited on-board resources such as storage and telemetry. Meanwhile, the impact of compression on scie...
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ISBN:
(纸本)0780332598
Considering the forthcoming spaceborne imaging instruments, on-board image compression is now essential due to the limited on-board resources such as storage and telemetry. Meanwhile, the impact of compression on scientific data must be analyzed and characterized in detail. The commonly used JPEG technique (based on a Discrete Cosine Transform) produces an undesirable blocking effect. Therefore, this paper presents an on-board compression system based on wavelet transform.
Transform methods have played an important role in signal and imageprocessingapplications. Recently, Selesnick has constructed the new orthogonal discrete wavelet transform, called the slantlet wavelet, with two zer...
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ISBN:
(纸本)0819452017
Transform methods have played an important role in signal and imageprocessingapplications. Recently, Selesnick has constructed the new orthogonal discrete wavelet transform, called the slantlet wavelet, with two zero moments and with improved time localization. The discrete slantlet wavelet transform is carried out by an existing filterbank which lacks a tree structure and has a complexity problem. The slantlet wavelet has been successfully applied in compression and denoising. In this paper, we present a new class of orthogonal parametric fast Haar slantlet transform system where the slantlet wavelet and Haar transforms are special cases of it. We propose designing the slantlet wavelet transform using Haar slantlet transform matrix. A new class of parametric filterbanks is developed. The behavior of the parametric Haar slantlet transforms in signal and image denoising is presented. We show that the new technique performs better than the slantlet wavelet transform in denoising for piecewise constant signals. We also show that the parametric Haar slantlet transform performs better than the cosine and Fourier transforms for grey level images.
In this paper, we consider classes of not bandlimited signals, namely, streams of Diracs and piecewise polynomial signals, and show that these signals can be sampled and perfectly reconstructed using wavelets as sampl...
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ISBN:
(纸本)0819450804
In this paper, we consider classes of not bandlimited signals, namely, streams of Diracs and piecewise polynomial signals, and show that these signals can be sampled and perfectly reconstructed using wavelets as sampling kernel. Due to the multiresolution structure of the wavelet transform, these new sampling theorems naturally lead to the development of a new resolution enhancement algorithm based on wavelet footprints.(2) Preliminary results show that this algorithm is also very resilient to noise.
In this paper, we study unsupervised image segmentation using wavelet-domain hidden Markov models (HMMs), where three clustering methods are used to obtain the initial segmentation results. We first review recent supe...
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ISBN:
(纸本)0819450804
In this paper, we study unsupervised image segmentation using wavelet-domain hidden Markov models (HMMs), where three clustering methods are used to obtain the initial segmentation results. We first review recent supervised Bayesian image segmentation algorithms using wavelet-domain HMMs. Then, a new unsupervised segmentation approach is developed by capturing the likelihood disparity of different texture features with respect to wavelet-domain HMMs. Three clustering methods, i.e., K-mean, soft clustering and multiscale clustering, are studied to convert the unsupervised segmentation problem into the self-supervised process by identifying the reliable training samples. The simulation results on synthetic mosaics and real images show that the proposed unsupervised segmentation algorithms can achieve high classification accuracy.
We present a unified image compressor with spline biorthogonal wavelets and dyadic rational filter coefficients which gives high computational speed and excellent compression performance. Convolutions with these filte...
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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 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.
This paper presents a new approach to demosaicing of spatially sampled image data observed through a color filter array, in which properties of Smith-Barnwell filterbanks are employed to exploit the correlation of col...
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ISBN:
(纸本)9781424407286
This paper presents a new approach to demosaicing of spatially sampled image data observed through a color filter array, in which properties of Smith-Barnwell filterbanks are employed to exploit the correlation of color components in order to reconstruct a subsampled image. The method is shown to be amenable to wavelet-domain denoising prior to demosaicing, and a general framework for applying existing image denoising algorithms to color filter array data is also described. Results indicate that the proposed method performs on a par with the state of the art for far lower computational cost, and provides a versatile, effective, and low-complexity solution to the problem of interpolating color filter array data observed in noise.
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.
In this paper, we propose a new combined harmonic-wavelet representation for audio where a harmonic analysis-synthesis scheme is used, first, to approximate each audio frame as a sum of several sinusoids. Then, the di...
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ISBN:
(纸本)0818679204
In this paper, we propose a new combined harmonic-wavelet representation for audio where a harmonic analysis-synthesis scheme is used, first, to approximate each audio frame as a sum of several sinusoids. Then, the difference between the original signal and the reconstructed harmonic signal is analyzed using a wavelet filtering scheme. After each step (harmonic analysis & wavelet filtering), parameters are quantized and encoded. Compared to previously proposed methods, our audio coder uses different harmonic analysis-synthesis and wavelet filtering schemes. We use the Total Least Squares (TLS)-Prony algorithm for the harmonic analysis-scheme, and an M-band wavelet transform for analyzing the residual. Altogether, our proposed coder is capable of delivering excellent audio signal quality at encoder bitrates of 60-70 kb/s.
This paper introduces a class of wavelet packets based upon a set of biorthogonal basis functions. Using a Kronecker product formulation, we develop a self-similar factorization that obeys a set of perfect reconstruct...
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ISBN:
(纸本)0819450804
This paper introduces a class of wavelet packets based upon a set of biorthogonal basis functions. Using a Kronecker product formulation, we develop a self-similar factorization that obeys a set of perfect reconstruction conditions. This construction is then identified as a wavelet packet decomposition and is applied to the finite field case. Finally, it is demonstrated that the proposed wavelet packets can be applied as a well-known class of error control codes.
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