The objective of multiple description coding (MDC) is to encode a single information source into multiple bitstreams, in a manner that the reconstructed source can be produced at different qualities according to the a...
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ISBN:
(纸本)9781538671207
The objective of multiple description coding (MDC) is to encode a single information source into multiple bitstreams, in a manner that the reconstructed source can be produced at different qualities according to the amount of bitstreams received at the decoder. In this paper, we propose to employ an optimal filtering strategy as a post processing method for a multiple description transform coding (MDTC) approach which utilizes discrete wavelet transform (DWT). Experimental results show that the proposed approach provides better results compared to existing approaches in the literature.
In this paper, the wavelet transform is used for the purpose of noise reduction and signal enhancement in order to aid in the detection of randomly occurring short duration signals in noisy environments with signal to...
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ISBN:
(纸本)0819411973
In this paper, the wavelet transform is used for the purpose of noise reduction and signal enhancement in order to aid in the detection of randomly occurring short duration signals in noisy environments with signal to noise ratios of about -30 dB. The noise is characterized as being additive and consists of correlated interference as well as Gaussian noise. Such problems are encountered in many applications, such as health diagnostics (e.g. electrocardiograms, echo-cardiograms and electroencephalograms), underwater acoustics and geophysical applications where a signature signal passes through multiple media. The wavelet transform, with its basis functions localized both in time and frequency, provides the user with a signal representation suitable for detection purposes. Following the introduction, a brief description of the problem with the characteristics of the signal to be detected and the noise that is present in the environment is given. Then, background information on the wavelet transform is presented. Finally, our results obtained by applying the wavelet transform to signal detection are shown.
The traditional mean-squared-error (MSE) or peak-signal-to-noise-ratio (PSNR) error measures are mainly focused on the pixel-by-pixel difference between the original and compressed images. Such metrics are improper fo...
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ISBN:
(纸本)0819425915
The traditional mean-squared-error (MSE) or peak-signal-to-noise-ratio (PSNR) error measures are mainly focused on the pixel-by-pixel difference between the original and compressed images. Such metrics are improper for subjective quality or fidelity assessment, since human perception is very sensitive to correlations between adjacent pixels. In this work, we explore the Haar wavelet to model the space-frequency localization property of human visual system (HVS). It is shown that the physical contrast in different resolutions can be easily represented in terms of transform coefficients. We model HVS with the Haar filter with several Visual mechanisms and develop a subjective quality measure which is more consistent with human observation experience.
image segmentation aims at partitioning an image into its constituent parts, which plays a crucial role in practical applications. In this paper, we present a wavelet frame-based model for color images segmentation, w...
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ISBN:
(纸本)9781728136608
image segmentation aims at partitioning an image into its constituent parts, which plays a crucial role in practical applications. In this paper, we present a wavelet frame-based model for color images segmentation, which can be regarded as a discretization to the classical Chan-Vese (C-V) model. The advantage of the wavelet frame-based approach is that it has fast algorithm and is able to extract important features of the input images. We then apply the alternating direction method of multipliers (ADAM) algorithm to solve the model. The experiments on some color image segmentation tasks indicate that our algorithm performs favorably against several existing methods.
This paper discusses the utility of scale-angle continuous wavelet transform (CWT) features for object classification. Theses features are used as input to two algorithms: character recognition and target recognition ...
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ISBN:
(纸本)0819432997
This paper discusses the utility of scale-angle continuous wavelet transform (CWT) features for object classification. Theses features are used as input to two algorithms: character recognition and target recognition in FLIR images. The corresponding recognition algorithm is robust against noise and allows data reduction. A comparative study is made between two types of directional wavelets derived from the Mexican hat wavelet and the usual template matching.
Two-dimensional wavelet analysis with directional frames is well-adapted and efficient, for detecting oriented features in images. but, for (quasi-) isotropic components, it is unnecessarily redundant. Using wavelets ...
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ISBN:
(纸本)0819450804
Two-dimensional wavelet analysis with directional frames is well-adapted and efficient, for detecting oriented features in images. but, for (quasi-) isotropic components, it is unnecessarily redundant. Using wavelets with variable angular selectivity leads to a prohibitive computing cost in the continuous wavelet formalism. We propose here a solution based on a multiresolution analysis in the angular variable (transferred from a biorthogonal analysis on the line), in Addition to the usual multiresolution in scale. The resulting scheme is efficient and competitive with traditional methods. Some applications are given to image denoising.
We propose wavelet ANOVA, a simple general-purpose statistical method for analysis of signals and images. We emphasize the application of the method to functional magnetic resonance imaging (fMRI). wavelet ANOVA combi...
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ISBN:
(纸本)0819432997
We propose wavelet ANOVA, a simple general-purpose statistical method for analysis of signals and images. We emphasize the application of the method to functional magnetic resonance imaging (fMRI). wavelet ANOVA combines the false discovery rate (FDR) approach to multiple comparisons with block wavelet thresholding and linear statistical models. We discuss the relationship of wavelet ANOVA to a similar method of Ruttimann, et al. We illustrate the application of wavelet ANOVA to analysis of an fMRI data set.
In this paper, a new prediction based method, predictive depth coding (PDC), for lossy waveletimage compression is presented. It compresses a wavelet pyramid composition by predicting the number of significant bits i...
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ISBN:
(纸本)0819432997
In this paper, a new prediction based method, predictive depth coding (PDC), for lossy waveletimage compression is presented. It compresses a wavelet pyramid composition by predicting the number of significant bits in each wavelet coefficient quantized by the universal scaler quantization and then by coding the prediction error with arithmetic coding. The adaptively found linear prediction context covers spatial neighbors of the coefficient to be predicted and the corresponding coefficients on lower scale and in the different orientation pyramids. In addition to the number of significant bits, the sign and the bits of non-sere coefficients are coded, The compression method is tested with a standard set of images and the results are compared with SFQ, SPIHT, EZW and context based algorithms. Even though the algorithm is very simple and it does not require any extra memory, the compression results are relatively good.
In this paper, an image-adaptive watermarking technique based upon a redundant wavelet transform is proposed. The redundant transform provides an overcomplete representation of the image which facilitates the identifi...
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ISBN:
(纸本)0780367251
In this paper, an image-adaptive watermarking technique based upon a redundant wavelet transform is proposed. The redundant transform provides an overcomplete representation of the image which facilitates the identification of significant image features via a simple correlation operation across scales. Although the watermarking algorithm is image adaptive, it is not necessary for the original image to be available for successful detection of the watermark. The performance and robustness of the proposed technique is tested by applying common image-processing operations such as filtering, requantization, and JPEG compression. A quantitative measure is proposed to objectify performance;under this measure, the proposed technique outperforms a wavelet scheme based on the usual critically sampled DWT.
A class of adaptive wavelet transforms that map integers to integers based on the adaptive update lifting scheme is presented. The main feature in the adaptive update lifting scheme is that the update lifting step, wh...
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ISBN:
(纸本)0819450804
A class of adaptive wavelet transforms that map integers to integers based on the adaptive update lifting scheme is presented. The main feature in the adaptive update lifting scheme is that the update lifting step, which is considered as an averaging operator and is performed prior to the prediction step, is adapted to the underlying signal content and the adaptivity decisions can be recovered at the synthesis transform without bookkeeping of the adaptivity decisions. The perfect reconstruction criterion for the integer realisation of such transforms are presented in this paper. These adaptive integer-to-integer wavelet transforms can be used in scalable lossless image coding applications. The lossless image coding and spatially scalable decoding performances are demonstrated.
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