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Undecimated Dual-Tree Complex wavelet Transforms

signal processing-image COMMUNICATION 2015年 35卷 61-70页

作者： Hill, P. R. Anantrasirichai, N. Achim, A. Al-Mualla, M. E. Bull, D. R. Univ Bristol Dept Elect & Elect Engn Bristol BS8 1UB Avon England Khalifa Univ Sci Technol & Res KUSTAR Abu Dhabi U Arab Emirates

Two undecimated forms of the Dual Tree Complex wavelet Transform (DT-CWT) are introduced together with their application to image denoising and robust feature extraction. These undecimated transforms extend the DT-CWT through the removal of downsampling of filter outputs together with upsampling of the complex filter pairs in a similar structure to the Undecimated Discrete wavelet Transform (UDWT). Both developed transforms offer exact translational invariance, improved scale-to-scale coefficient correlation together with the directional selectivity of the DT-CWT. Additionally, within each developed transform, the subbands are of a consistent size. They therefore benefit from a direct one-to-one relationship between co-located coefficients at all scales and therefore this offers consistent phase relationships across scales. These advantages can be exploited within applications such as denoising, image fusion, segmentation and robust feature extraction. The results of two example applications (bivariate shrinkage denoising and robust feature extraction) demonstrate objective and subjective improvements over the DT-CWT. The two novel transforms together with the DT-CWT offer a trade-off between denoising performance, computational efficiency and memory requirements. (C) 2015 Elsevier B.v. All rights reserved.

关键词： Discrete wavelet Transforms image denoising

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A wavelet filter bank which minimizes a novel translation invariant discrete uncertainty measure 5

A wavelet filter bank which minimizes a novel translation in...

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5th IEEE Southwest Symposium on image Analysis and Interpretation

作者： Tay, P Havlicek, JR DeBrunner, v Univ Oklahoma Sch Elect & Comp Engn Norman OK 73019 USA

ISBN: (纸本)0769515371

We develop a novel measure of joint time-frequency localization applicable to equivalence classes of finite-length discrete signals, which are of increasing importance in modern signal and image processing applications. Like the well-known Heisenberg-Weyl uncertainty principle that quantifies joint localization for continuous signals, this new measure is translation invariant and admits an intuitively satisfying interpretation in terms of the statistical variance of signal energy in time or space and in frequency. The new measure is used to design a now low-pass wavelet analysis filter with optimal joint localization. This new filter is then used to construct a localized separable 2-D discrete wavelet transform which is demonstrated on several images of general interest in practical applications.

关键词： Discrete wavelet transforms Energy measurement Extraterrestrial measurements Filter bank Frequency measurement image processing signal processing Time frequency analysis Time measurement wavelet analysis

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High Security image Steganography Using IWT and Graph Theory

High Security Image Steganography Using IWT and Graph Theory

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3rd IEEE International conference on signal and image processing applications (ICSIPA)

作者： Thanikaiselvan, v Arulmozhivarman, P. VIT Univ Sch Elect Engn Vellore 632014 Tamil Nadu India

ISBN: (纸本)9781479902699;9781479902675

Steganography conceals the secret information inside the cover medium. There are two types of steganography techniques available practically. They are spatial domain steganography and Transform domain steganography. The objectives to be considered in the steganography methods are high capacity, imperceptibility and robustness. In this paper, a Color image steganography in transform domain is proposed. Reversible Integer Haar wavelet transform is applied to the R, G and B planes separately and the data is embedded in a random manner. Random selection of wavelet coefficients is based on the graph theory. This proposed system uses three different keys for embedding and extraction of the secret data, where key1(Subband Selection - SB) is used to select the wavelet subband for embedding, key2(Selection of Co-effecients-SC) is used to select the co-efficients randomly and key3 (Selection of Bit length-SB) is used to select the number of bits to be embedded in the selected co-efficients. This method shows good imperceptibility, High capacity and Robustness.

关键词： Steganography IWT (Integer wavelet Transform) Graph Theory LSB(Least Significant Bit) substitution Steganalysis

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wavelet signal processing applied to Optical Phase Conjugation

Wavelet signal processing applied to Optical Phase Conjugati...

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conference on wavelets - applications in signal and image processing IX

作者： Jones, KJ Rice Univ Dept Math Houston TX 77005 USA

ISBN: (纸本)0819441929

wavelet signal processing has demonstrated remarkable capabilities in reducing noise, achieving better resolution through edge detection and increasing data transmission by means of data compression. While wavelets are digital, another field, Optical Phase Conjugation (OPC), is analog and has been applied to similar problems: signal and image distortion reduction and optical data storage. wavelets have been applied to optical solitons, laser beam diagnostics, diode laser arrays, interferometry and optical correlators. wavelet signal processing will be applied to Optical Phase Conjugation to examine laser beam interaction in nonlinear crystals and remove distortion from input and output laser beams.

关键词： wavelet signal processing optical phase conjugation optical data storage noise reduction Morlet wavelets photorefractive memories

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Edge-Based image Watermarking Method with Weighted Discrete Cosine Transform Coefficients 30

Edge-Based Image Watermarking Method with Weighted Discrete ...

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30th IEEE signal processing and Communications applications conference (SIU)

作者： Karakis, Rukiye Gurkahraman, Kali Sivas Cumhuriyet Univ Yazihm Muhendisligi Bolumu Sivas Turkey Sivas Cumhuriyet Univ Bilgisayar Muhendisligi Bolumu Sivas Turkey

ISBN: (纸本)9781665450928

In image watermarking, hybrid approaches increase imperceptibility and robustness. Also, a scaling factor is used, which should be optimized when combining the cover image and watermark. In this study, discrete wavelet transform and discrete cosine transform (DCT) were used together. The watermark-edge image was obtained by randomly inserting the watermark on the horizontal, vertical and diagonal edge points of the cover image detected with Sobel. The DCT frequency components of the watermark-edge image were weighted with a generated matrix and combined with the DCT of the cover image. According to the obtained results, the proposed method is imperceptible and robust to various attacks, especially JPEG compression and noise attacks.

关键词： image watermarking edge detection scaling factor discrete wavelet transform discrete cosine transform

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Multiple feature based multiscale image enhancement 14

Multiple feature based multiscale image enhancement

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14th International conference on Digital signal processing (DSP 2002)

作者： Capdiferro, L Casieri, v Laurenti, A Jacovitti, G Fdn Ugo Bordoni I-00142 Rome Italy

ISBN: (纸本)0780375033

A novel technique for image enhancement based on a multiscale pyramid is presented. It generalizes classical edge-oriented wavelet based enhancement technique by employing multiple wavelets features. visually relevant features are amplified in the wavelet domain according to a pointwise multiscale product. The use of complex in phase-quadrature wavelets allows to emphasize anyway oriented features.

关键词： enhancement multiscale circular harmonic wavelet

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image denoising using orthonormal finite ridgelet transform

Image denoising using orthonormal finite ridgelet transform

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conference on wavelet applications in signal and image processing vIII

作者： Do, MN vetterli, M Ecole Polytech Fed Lausanne LCAV CH-1015 Lausanne Switzerland

ISBN: (纸本)0819437646

This paper addresses the image denoising problem using a newly proposed digital image transform: the finite ridgelet transform (FRIT). The transform is invertible, non-redundant and achieved via fast algorithms. Furthermore this transform can be designed to be orthonormal thus indicating its potential in many other image processing applications. We then propose various improvements on the initial design of the FRIT in order to make it to have better energy compaction and to reduce the border effect. Experimental results show that the new transform outperforms wavelets in denoising images with linear discontinuities.

关键词： wavelets Discrete wavelet transforms Denoising Radon transform image denoising wavelet transforms Fourier transforms Radon Digital imaging image processing

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A new approach to pre-processing digital image for wavelet-based watermark

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2008年第2期221卷 274-283页

作者： Agreste, Santa Andaloro, Guido Univ Messina Dept Math I-98166 Messina Italy

The growth of the Internet has increased the phenomenon of digital piracy, in multimedia objects, like software, image, video, audio and text. Therefore it is strategic to individualize and to develop methods and numerical algorithms, which are stable and have low computational cost, that will allow us to find a solution to these problems. We describe a digital watermarking algorithm for color image protection and authenticity: robust, not blind, and wavelet-based. The use of Discrete wavelet Transform is motivated by good time-frequency features and a good match with Human visual System directives. These two combined elements are important for building an invisible and robust watermark. Moreover our algorithm can work with my image, thanks to the step of pre-processing of the image that includes resize techniques that adapt to the size of the original image for wavelet transform. The watermark signal is calculated in correlation with the image features and statistic properties. In the detection step we apply a re-synchronization between the original and watermarked image according to the Neyman-Pearson statistic criterion. Experimentation on a large set of different images has been shown to be resistant against geometric, filtering, and StirMark attacks with a low rate of false alarm. (C) 2007 Elsevier B.v. All rights reserved.

关键词： Copyright protection Digital watermark Discrete wavelet transform image processing

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image splicing detection with dwt domain extended Markov features 26

Image splicing detection with dwt domain extended Markov fea...

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26th IEEE signal processing and Communications applications conference, SIU 2018

作者： Yildirim, Esra Odabas Ulutas, Guzin Bilgisayar Muhendisliǧi Bolumu Ataturk Universitesi Erzurum Turkey Bilgisayar Muhendisliǧi Bolumu Karadeniz Teknik Universitesi Trabzon Turkey

ISBN: (纸本)9781538615010

Recently, image forgery has increased with the widespread of using digital images. At least two different images are used when forged images are generated in image splicing which is an image forgery method. Forged and original images are detected with features extracted from the image. In this study, a Discrete wavelet Transform and Markov based method is used to extract/construct feature vectors. Firstly, with applying Discrete wavelet Transform to the image low frequency component image is obtained, later four-direction Markov features are extracted from the low frequency component image. After the feature extraction, images are classified as forged and original with support vector machines. The method has been tested for accuracy ratio in the commonly used data sets (Casia v1.0, Casia v2.0, Columbia DvMM) in image Splicing Detection. In the experimental results, it was seen that forged and orjinal images are detected with high accuracy ratio compared with the similar methods in the literature. © 2018 IEEE.

关键词： Discrete wavelet transforms

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image classification based on complex wavelet structural similarity

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signal processing-image COMMUNICATION 2013年第8期28卷 984-992页

作者： Rehman, Abdul Gao, Yang Wang, Jiheng Wang, Zhou Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

Complex wavelet structural similarity (CW-SSIM) index has been recognized as a novel image similarity measure of broad potential applications due to its robustness to small geometric distortions such as translation, scaling and rotation of images. Nevertheless, how to make the best use of it in image classification problems has not been deeply investigated. In this paper, we introduce a series of novel image classification algorithms based on CW-SSIM and use handwritten digit recognition, and face recognition as examples for demonstration. Among the proposed approaches, the best compromise between accuracy and complexity is obtained by the CW-SSIM support vector machine based algorithms, which combines an unsupervised clustering method to divide the training images into clusters with representative images and a supervised learning method based on support vector machines to maximize the classification accuracy. Our experiments show that such a conceptually simple image classification method, which does not involve any registration, intensity normalization or sophisticated feature extraction processes, and does not rely on any modeling of the image patterns or distortion processes, achieves competitive performance with reduced computational cost. (C) 2012 Elsevier B.v. All rights reserved.

关键词： Complex-wavelet structural similarity image classification Handwritten digit recognition Face recognition Clustering Support vector machine

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