in wavelets based coding applications, resolution scalability is achieved by retaining the low pass signal subband corresponds to the required resolution and discarding other high pass wavelet subbands. Aliasing is a ...
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ISBN:
(纸本)0780391349
in wavelets based coding applications, resolution scalability is achieved by retaining the low pass signal subband corresponds to the required resolution and discarding other high pass wavelet subbands. Aliasing is a common problem present in such downsampling. In this paper a novel technique for improving the low pass filter for improved downsampling is presented. This method uses an extra update step followed by P+U lifting scheme. The preprocessing update step is chosen as the dual update step associated with the wavelet. The spatially adaptive low pass (SALP) filtering concept is used for the second update step, leading to an overall low pass filter whose size adapts to the underlying signal content. The filter choices for the second update step is recovered at the decoder without any bookkeeping. Results using the 2D 5/3 wavelet with the extra pre-processing update step show improvements over conventional wavelets.
作者：
Rajmic, PBrno Univ Technol
Fac Elect Engn & Commun Technol Dept Telecommun Brno 61200 Czech Republic
The new method of segmented wavelet transform (SegWT) makes it possible to compute the discrete-time wavelet transform of a signal segment-by-segment. This means that the method could be utilized for wavelet-type proc...
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ISBN:
(纸本)3540312579
The new method of segmented wavelet transform (SegWT) makes it possible to compute the discrete-time wavelet transform of a signal segment-by-segment. This means that the method could be utilized for wavelet-type processing of a signal in "real time", or in case we need to process a long signal (not necessarily in real time), but there is insufficient computational memory capacity for it (for example in the signal processors). Then it is possible to process the signal part-by-part with low memory costs by the new method. The method is suitable also for the speech processing, e.g. denoising the speech signal via thresholding the wavelet coefficients or speech coding. In the paper, the principle of the segmented forward wavelet transform is explained and the algorithm is described in detail.
Discrete wavelet transform is a powerful mathematical tool used for signal and image compression, nonlinear filtering or noise reduction, signal and biomedical imageprocessing and all kind of applications that implie...
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images are often corrupted as a result of various factors that can occur during acquisition and transmission processes. image denoising is aimed at removing or reducing the noise so that a good-quality image can be ob...
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In this paper an image compression technique which is designed for high compression ratios is presented. The discrete wavelet transform (DWT) is combined with Lloyd Max (LM) quantization and zerotree wavelet (ZTW) str...
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Several approaches have been proposed to improve the compaction performance of the wavelet transform by taking into account the singularities present in the image and their 2D directionalities. This improvement is val...
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ISBN:
(纸本)1604238216
Several approaches have been proposed to improve the compaction performance of the wavelet transform by taking into account the singularities present in the image and their 2D directionalities. This improvement is valid both for compression and de-noising applications. Here, we investigate an edge adaptive wavelet transform which has a better rate-distortion characteristic than the classical wavelet transform. The proposed approach can be viewed roughly as a combination of image segmentation and shape adaptive wavelet transform. The algorithm consists of two steps. In the first step we locate edges by using a sigma filter. In the second step we apply the modified wavelet transform on the separated parts of the image. We provide performance results in terms of rate-distortion curves for both 1D and relatively simple 2D signals.
In this paper, we propose a new method for estimation of the number of embedding changes for non-adaptive +/- k embedding in images. By modeling the cover image and the stego noise as additive mixture of random proces...
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ISBN:
(纸本)0819456543
In this paper, we propose a new method for estimation of the number of embedding changes for non-adaptive +/- k embedding in images. By modeling the cover image and the stego noise as additive mixture of random processes, the stego message is estimated from the stego image using a denoising filter in the wavelet domain. The stego message estimate is further analyzed using ML/MAP estimators to identify the pixels that were modified during embedding. For non-adaptive +/- k embedding, the density of embedding changes is estimated from selected segments of the stego image. It is shown that for images with a low level of noise (e.g., for decompressed JPEG images) this approach can detect and estimate the number of embedding changes even for small values of k, such as k=2, and in some cases even for k=1.
In this study, we propose a method based on wavelet domain median filter (WDMF) for the image enhancement. The method is performed by transforming corruted image into wavelet domain and filtering the image by median f...
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In this paper, we discuss some of the leading issues in through the wall radar imaging (TWRI) problems. We focus on the primary system challenges and deliverables, dealing only with the applications of statistical sig...
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ISBN:
(纸本)081945804X
In this paper, we discuss some of the leading issues in through the wall radar imaging (TWRI) problems. We focus on the primary system challenges and deliverables, dealing only with the applications of statistical signal and array processing. applications of antenna design and electromagnetic propagation are equally important, but they are both outside the scope of this paper. The material presented considers key desirable TWRI system properties and features and provides candidate solutions to achieve them. We focus on research performed at Villanova University and demonstrate some of our recent approaches to address system functionalities and requirements using analyses, computer simulations, and real-data. The paper does not attempt to cover all progress made in the field to date nor does it intend to compare the proposed techniques with alternative and competitive methods. It is written with the primary purpose of bringing to the reader many leading challenges and diverse issues worthy of considerations.
The wavelet transform is a very powerful tool for image coding for which the quality of the compression is depending on the choice of the filter banks associated to the wavelet. These filters can be characterized by t...
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ISBN:
(纸本)1604238216
The wavelet transform is a very powerful tool for image coding for which the quality of the compression is depending on the choice of the filter banks associated to the wavelet. These filters can be characterized by two indices: a spatial index related to their significant support and a frequency index related to their aliasing. This work explores the connection between a quality criteria and these two indices for a given image family. Two useful applications are presented: in the first one a neural network allows us to deduce the best filter bank for a given image. In the second one a quality criterion for a new image is estimated knowing the filter bank.
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