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A new wavelet based compression scheme replicating human visual system processing

A new wavelet based compression scheme replicating human vis...

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7th International conference on Computational Intelligence and Multimedia applications

作者： Sreelekha, G. Sathidevi, P. S. Natl Inst Technol Dept Elect Engn Calicut Kerala India

ISBN: (纸本)0769530508

A perceptual image coder for the compression of monochrome images is presented here, in which the coding structure is coupled with a vision model to produce coded images with an improved visual quality at low bit-rates. The coder is an improvement on the current image compression standard, JPEG2000. The proposed coding structure incorporates the bunion vision model it? all stages of compression, and gives very good results compared to the existing wavelet based JPEG scheme. Though the mathematical model used are not new, the simple structure of it which can be easily incorporated into the coding structure of the JPEG2000, incorporates the visual processing stages in a very systematic manner in the same way as the visual neurons process the signal. The results presented in this paper reveal that the proposed structure gives very good perceptual quality compared to the existing scheme especially as we go for lower bit rates. One of the major advantages of the proposed scheme is that it can be easily extended to a structure in which the rate control optimization can be incorporated, as in the JPEG2000.

关键词： image compression

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Clouds removal from remotely sensed images by using a bandelet-based reconstruction technique

Clouds removal from remotely sensed images by using a bandel...

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conference on wavelet applications in Industrial processing V

作者： Maalouf, Aldo Carre, Philippe Augereau, Bertrand Fernandez-Maloigne, Christine Univ Politiers Signal Image Communicat Lab F-86962 Futuroscope France

ISBN: (纸本)9780819469236

The recurrent presence of clouds and clouds shadows in aerial or remotely sensed images is an awkward problem that severely limits the regular exploitations capability of these images. Removing cloud-contaminated portions of the image and then filling in the missing data represent an important photo editing cumbersome task. The intent of this work is to propose a technique for the reconstruction of areas obscured by clouds in a remotely sensed image. To this end, a new efficient reconstruction technique for missing data synthesis is presented. This technique is based on the Bandelet transform and the multiscale geometrical grouping. It consists of two steps. In the first step, the curves of geometric flow of different zones of the image are determined by using the Bandelet transform with multiscale grouping. This step allows a better representation of the multiscale geometry of the image's structures. Having well represented this geometry, the information inside the cloud-contaminated zone is synthesized by propagating the geometrical flow curves inside that zone. This step is accomplished by minimizing, a functional whose role is to reconstruct the missing or cloud contaminated zone independently of the size and topology of the reconstruction or inpainting domain. Thus, the flow lines are well tied inside the cloud-contaminated zone. The proposed technique is illustrated with some examples on processing multispectral aerial images. The obtained results are compared with those obtained by other clouds removal techniques.

关键词： Clouds wavelets image classification image processing Reconstruction algorithms wavelet transforms image segmentation Lithium Remote sensing Multispectral imaging

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wavelet denoising before support vector classification of hyperspectral images

Wavelet denoising before support vector classification of hy...

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IEEE 15th signal processing and Communications applications conference

作者： Demir, Beguem Ertuerk, Sarp Kocaeli Univ Elekt Haberlesme Muhendisligi Bolumu Veziroglu Ye TR-41040 Izmit Turkey

ISBN: (纸本)9781424407194

Hyperspectral image classification using support vector machines (SVM) after wavelet domain denoising is proposed in this paper. In the proposed approach, hyperspectral images are classified using SVM after noise reduction is carried out in each band independent of other bands using spatially adaptive Bayesian shrinkage. It is shown that support vector machine classification of denoised hyperspectral images gives significantly better classification accuracy and furthermore improves sparsity. Therefore this approach has faster testing time, compared with direct SVM based classification. This feature makes the denoised SVM based hyperspectral classification approach more suitable for applications that require low-complexity, and possibly real-time classification.

关键词： Support vector machines

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wavelet based uneven illumination compensation for defect detection of flat panel display

Wavelet based uneven illumination compensation for defect de...

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4th IASTED International conference on signal processing, Pattern Recognition, and applications, SPPRA 2007

作者： Sang, Ji Kim Nam, Yoo Kim Byung, Gook Lee Joon, Jae Lee Division of Image Contents School of Design and IT San69-1 Jurye2-dong Sasang-gu Busan 617-716 Korea Republic of

ISBN: (纸本)9780889866461

FPD(Flat panel displays) are becoming widely acceptable and popular as display devices growing at a rapid pace and making it a promising investment opportunity. Display quality is part of the final FPD inspection process prior to shipping. FPD devices have non-uniform background intensity, and shape and intensity of defects are very various. Due to the uneven illumination of panels it is difficult to detect the defects, Therefore this paper proposes a uneven illumination compensation method using wavelet based multi-resolution structure. This is first done by decomposing the image into multi-resolution levels and selecting some band frequency sub-bands by removing lower sub-bands and higher sub-bands corresponding to low varying signal and high frequency random noise, respectively, resulting in flat background images in reconstruction. A simple binary thresholding technique is then used to separate the defective regions from the restored image. Finally, blob analysis as post-processing is carried out to get rid of false defects.

关键词： Flat panel displays

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Line edge roughness measurement of nanostructures in SEM metrology by using statistically matched wavelet

Line edge roughness measurement of nanostructures in SEM met...

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conference on wavelet applications in Industrial processing V

作者： Midoh, Yoshihiro Nakamae, Koji Fujioka, Hirornu Osaka Univ Grad Sch Informat Sci & Technol Dept Informat Syst Engn 2-2 Yamadaoka Suita Osaka 5650871 Japan Fukui Univ Technol Dept Management & Informat Sci Fukui Fukui 9108505 Japan

ISBN: (纸本)9780819469236

As the dimensions of integrated circuit devices continue to shrink, the effect of line edge roughness (LER) of resist patterns on the device performance is becoming a serious problem. Therefore, the desire to measure LER with more accuracy is growing. We have proposed the method for LER measurement by using the wavelet multiresolution analysis. It is still required that a wavelet filter is optimized to reveal line edges from noisy SEM signal profile to achieve more accuracy. In this paper, we try to estimate statistically a wavelet that is matched to measure LER from the scanning electron microscopy (SEM) signal profile. Here we propose a novel mathematical and statistical modeling of the SEM signal profile. The mathematical model has been deduced from a variety of SE signal shapes which have been calculated by Monte Carlo simulations. It is also necessary to consider statistical effects such as the property of the atoms within the nanostructures and the fluctuation of the exposure. We then formulate a model by considering four characteristics of critical dimension (CD) in photolithography: the exponential distribution of the image intensity around the impinging electron beam, the spatial frequency distribution of LER, phase difference between both sides of a line pattern, and shot noise in SEM images. Statistically matched wavelet is estimated from local signal profiles around true edge positions. As a result, it was seen that there was a high degree of similarity between real and model SEM images. We also compared performance in accuracy of CD measurement between the matched wavelet and the first-order derivative Gaussian wavelet, which has selected as the most suitable one for lithography metrology in previous work. CDs measured by both wavelets were almost equal since the matched wavelet has relatively small effect on noise reduction.

关键词： matched wavelet wavelet multiscale edge detection line edge roughness critical dimension SEM

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Bit-plane analysis and contexts combining of JPEG2000 contexts for on-board satellite image compression

Bit-plane analysis and contexts combining of JPEG2000 contex...

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32nd IEEE International conference on Acoustics, Speech and signal processing

作者： Delaunay, X. Chabert, M. Morin, G. Charvillat, V. TeSA CNES NOVELTIS 14-16 Port St Etienne F-31000 Toulouse France IRIT ENSEEIHT F-31071 Toulouse 7 France

ISBN: (纸本)9781424407286

This paper studies the performance of the ZC contexts in JPEG2000. A quality criterion based on the mutual information is introduced. According to this criterion, there exist ZC contexts which are not effective in any bit-plane. They can thus be merged with others without significant loss of the compression efficiency. Since the contextual conditional probabilities strongly depend on the bit-planes, an adaptation of the contexts to the bit-planes is also proposed. First, an optimal context quantizer is used on each bit-planes, then a simple greedy entropy minimization procedure allows to combine the ZC contexts in JPEG2000. The results are compared with a global combination of JPEG2000 ZC contexts. Tests have been performed on a real satellite image data base. With only four ZC contexts, the PSNR is less than 0.01 dB lower than the PSNR with the nine ZC contexts.

关键词： image coding minimum entropy methods satellite applications wavelet transforms

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Improved adaptive lifting scheme for wavelet-based image compression

Improved adaptive lifting scheme for wavelet-based image com...

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3rd International conference on Intelligent Information Hiding and Multimedia signal processing

作者： Li, Qiong Li, Guo-Qiang He, Yi-Liang Niu, Xia-Mu Harbin Inst Technol Sch Elect Engn Harbin 150006 Peoples R China Harbin Inst Technol Dept Math Harbin 150006 Peoples R China

ISBN: (纸本)9780769529943

This paper investigates an adaptive lifting scheme for wavelet-based image compression, which performs update before prediction, and then we proposes an improved adaptive update and prediction scheme to better exploit the correlation among neighboring pixels. Simulation results show that the proposed scheme generates in the transformed domain lower coefficients' entropy, lower high-frequency coefficients' energy and more zero values, which make it useful for image compression applications.

关键词： image compression

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Local bivariate Cauchy distribution for video denoising in 3-D complex wavelet domain

Local bivariate Cauchy distribution for video denoising in 3...

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conference on applications of Digital image processing XXX

作者： Rabbani, Hossein Vafadust, Mansur Selesnick, Ivan Amirkabir Univ Technol Fac Biomed Engn Dept Bioelect Tehran Polytech 424 Hafez Ave Tehran Iran Polytech Univ Metrotech Ctr 6 Dept Elect & Comp Engn Brooklyn NY 11201 USA

ISBN: (纸本)9780819468444

In this paper, we present a new video denoising algorithm using bivariate Cauchy probability density function (pdf) with local scaling factor for distribution of wavelet coefficients in each subband. The bivariate pdf takes into account the statistical dependency among wavelet coefficients and the local scaling factor model the empirically observed correlation between the coefficient amplitudes. Using maximum a posteriori (MAP) estimator and minimum mean squared estimator (MMSE), we describe two methods for video denoising which rely on the bivariate Cauchy random variables with high local correlation. Because separate 3-D transforms, such as ordinary 3-D wavelet transforms (DWT), have artifacts that degrade their performance for denoising, we implement our algorithms in 3-D complex wavelet transform (DCWT) domain. In addition, we use our denoising algorithm in 2-D DCWT domain, where the 2-D transform is applied to each frame individually. The simulation results show that our denoising algorithms achieve better performance than several published methods both visually and in terms of peak signal-to-noise ratio (PSNR).

关键词： 3-D complex wavelet transform statistical modeling MAP estimator MMSE estimator

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Locally adaptive reconstruction of lost low frequency coefficients in wavelet coded images

Locally adaptive reconstruction of lost low frequency coeffi...

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conference on Visual Communications and image processing 2007

作者： Rombaut, Joost Pizurica, Aleksandra Philips, Wilfried Univ Ghent Dept TELIN St Pietersniuwstraat 41 B-9000 Ghent Belgium

ISBN: (纸本)9780819466211

In packet switched networks such as the Internet, packets may get lost during transmission due to, e.g., network congestion. This leads to a quality degradation of the original signal. As video communication is a bandwidth consuming application, the original data are first compressed. This compression step increases the impact of information loss even more. In wavelet based image and video coding, the low frequency data is the most important. Loss of low frequency coefficients results in annoying black holes in the received images and video. This effect can be countered by post processing error concealment: a lost coefficient is estimated from its neighboring coefficients. In this paper we present a locally adaptive interpolation method for the lost low frequency coefficients. For each lost low frequency coefficient, we estimate the optimal interpolation direction (horizontal or vertical) using novel error measures. In this way, we preserve the edges in the reconstructed image much better. Compared to older techniques of similar complexity, our scheme reconstructs images with the same or better quality. This is reflected in the visual as well as in the numerical results: there is an increase of up to 4.4 dB compared to bilinear concealment. The proposed scheme is fast and simple, which makes it suitable for real-time applications.

关键词： image reconstruction error concealment packet loss wavelet coding

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Robust multiresolution techniques for image reconstruction

Robust multiresolution techniques for image reconstruction

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8th conference on Biomedical Thermoacoustics, Optoacoustics and Acousto-optics

作者： Liebling, Michael CALTECH Beckman Inst Biol Imaging Ctr Pasadena CA 91125 USA

ISBN: (纸本)9780819465504

The reconstruction of images from projections, diffraction fields, or other similar measurements requires applying signal processing techniques within a physical context. Although modeling of the acquisition procedure can conveniently be carried out in the continuous domain, actual reconstruction from experimental measurements requires the derivation of discrete algorithms that are accurate, efficient, and robust. In recent years, wavelets and multiresolution approaches have been applied successfully for common image processing tasks bridging the gap between discrete and continuous representations. We show that it is possible to express many physical problems in a wavelet framework, thereby allowing the derivation of efficient algorithms that take advantage of wavelet properties, such as multiresolution structure, sparsity, and space-frequency decompositions. We review several examples of such algorithms with applications to X-ray tomography, digital holography, and confocal microscopy and discuss possible future extensions to other modalities.

关键词： image reconstruction wavelets splines tomography digital holography fresnelets confocal microscopy

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