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Hilbert quantum image scrambling and graph signal processing-based image steganography

MULTIMEDIA TOOLS AND applications 2022年第13期81卷 17817-17830页

作者： Sharma, Vijay Kumar Sharma, Prakash Chandra Goud, Harsh Singh, Arjun Manipal Univ Jaipur Sch Comp & Informat Technol Ajmer Rd Jaipur Rajasthan India Manipal Univ Jaipur Informat Technol Dept Ajmer Rd Jaipur Rajasthan India Indian Inst Informat Technol Elect & Commun Engg Dept Nagpur Maharashtra India

Steganography plays a big role in secret communication by concealing secret information in the carrier. This paper presents a graph signal processing-based robust image steganography technique for posting images over social networks. In the embedding, we first obtained a scrambled version of the secret image using quantum scrambling. Next, we applied graph wavelet transformation on both the cover image and scrambled secret image followed by alpha (alpha) blending on both image signals (cover image signal and scrambled image signal). Finally, inverse graph wavelet transformation of the resulting image was undertaken to obtain the stego image. In this paper, the use of graph wavelet transformation improved interpixel correlation, which resulted in the excellent visual quality of both the stego image and the extracted secret image. Our experiments show that the picture quality of both the cover image and the stego image is exactly the same.

关键词： Quantum image scrambling Alpha blending Graph signal processing Steganography Graph wavelet

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Multiresolution analysis with decimated wavelet transform for image zooming

Multiresolution analysis with decimated wavelet transform fo...

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Conference on wavelet applications in signal and image processing viii

作者： Nicolier, F Truchetet, F IUT Le Creusot Le2i F-71200 Le Creusot France

ISBN: (纸本)0819437646

Blurred images are produced by interpolation process. A wavelet-based magnification method is proposed that both increases the resolution of an image and adds local high-frequency informations, in order to provide digitally zoomed images with sharp edges. wavelet transforms computed by the decimated Mallat's algorithm present pyramidal aspect. This pyramidal analysis combined with a prediction of high-frequency coefficients is used to produce a magnified image. The prediction is based on a zero-crossings representation and on the construction of a multiscale edge-signature database. Performances are evaluated for synthetic and noisy images. A significant improvement regarding some classical methods (spline interpolation) is observed.

关键词： Reconstruction algorithms wavelets wavelet transforms Databases Fast wavelet transforms image processing image quality image resolution Resolution enhancement technologies signal processing

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MULTISCALE SYSTEM-THEORY

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND applications 1994年第1期41卷 2-15页

作者： BENVENISTE, A NIKOUKHAH, R WILLSKY, AS INRIA F-78153 LE CHESNAYFRANCE MIT LIDSCAMBRIDGEMA 02139

In many applications it is of interest to analyze and recognize phenomena occurring at different scales. The recently introduced wavelet transforms provide a time-and-scale decomposition of signals that offers the possibility of such an analysis. Until recently, however, there has been no corresponding statistical framework to support the development of optimal, multiscale statistical signal processing algorithms. A recent work of some of the present authors and co-authors proposed such a framework via models of ''stochastic fractals'' on the dyadic tree. In this paper we investigate some of the fundamental issues that are relevant to system theories on the dyadic tree, both for systems and signals.

关键词： signal resolution signal processing wavelet transforms Filtering Power system modeling image resolution Stochastic processes wavelet packets image processing wavelet analysis

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Tunable continuous wavelet and frame transforms

Tunable continuous wavelet and frame transforms

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Conference on wavelet applications in signal and image processing viii

作者： Scholl, JF Barker, DL Schmitt, HA Langan, JD Raytheon Elect Syst Tucson AZ 85734 USA

ISBN: (纸本)0819437646

Continuous wavelet transforms (CWT) and frames have always been useful for noise suppression, edge detection and medical signal processing. However these transforms are generally shied away from since computational complexity prevents their widespread use. However, recently developed processor technology that uses analog rather than digital signal processing hardware may be the ideal means to implement and apply these algorithms. It is then appropriate to consider new types of frames and continuous wavelet systems. We propose two families of tunable continuous wavelet systems with widely varying frame bounds and scaling behavior, and illustrate examples of computations involving these systems.

关键词： continuous wavelet transforms frames radial basis functions analog signal processing

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Framework for FPGA-based discrete biorthogonal wavelet transforms implementation

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IEE PROCEEDINGS-VISION image AND signal processing 2006年第6期153卷 721-734页

作者： Uzun, I. S. Amira, A. Queens Univ Belfast Sch Elect Elect & Comp Sci Belfast Antrim North Ireland Brunel Univ Sch Engn & Design Uxbridge UB8 3PH Middx England

The discrete wavelet transform has taken its place at the forefront of research for the development of signal and image processing applications. These wavelet-based approaches have outperformed existing strategies in many areas including telecommunication, numerical analysis and, most notably, image/video compression. The authors present an investigation into the design and implementation of 1-D and 2-D discrete biorthogonal wavelet transforms (DBWTs) using a field programmable gate array (FPGA)-based rapid prototyping environment. The proposed architectures for DBWTs are scalable, modular and have less area and time complexity when compared with existing structures. FPGA implementation results based on a Xilinx Virtex-2000E device have shown that the proposed system provides an efficient solution for the processing of DBWTs in real-time.

关键词： image processing FIELD programmable gate arrays PROGRAMMABLE logic devices BIORTHOGONAL systems FOURIER analysis waveletS (Mathematics)

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On the performance of integer wavelets for the lossy compression of smooth images

On the performance of integer wavelets for the lossy compres...

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Conference on wavelet applications in signal and image processing viii

作者： Grangetto, M Magli, E Olmo, G Politecn Torino Dipartimento Elettron I-10129 Turin Italy

ISBN: (纸本)0819437646

It is well known that the image compression task can be effectively accomplished by means of the wavelet transform. A new method has been recently proposed for the computation of this transform, i.e. the Lifting Scheme (LS). Besides being computationally more efficient than the classical filter bank scheme, the LS also enables the computation of a wavelet transform which maps integers to integers, so allowing for the design of joint lossless and lossy compression schemes. The performance of this Integer wavelet Transform (IWT) has already been studied in the literature, and compared to that of the Discrete wavelet Transform (DWT) in the lossy case;it has been found that in most cases the DWT achieves slightly better performance with respect to the DWT. In this paper we show that this result does not hold in the case of lossy compression of smooth images, as the IWT has a much larger loss of performance, making it ineffective for the compression of such images. We first select measures of image smoothness;then we study the IWT lossy compression performance in the presence of different degrees of smoothness, on an set containing various kinds of images. Finally, we relate the IWT compression performance to the degree of image smoothness.

关键词： lifting wavelet transform image coding

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Differential affine motion estimation for medical image registration

Differential affine motion estimation for medical image regi...

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Conference on wavelet applications in signal and image processing viii

作者： Periaswamy, S Weaver, JB Healy, DM Rockmore, DN Kostelec, PJ Farid, H Dartmouth Coll Dept Comp Sci Hanover NH 03755 USA

ISBN: (纸本)0819437646

We have applied techniques from differential motion estimation in the context of automatic registration of medical images. This method uses optical-flow and Fourier techniques for local/global registration. A six parameter affine model is used to estimate shear, rotation, scale and translation. We show the efficacy of this method with images of similar and different contrasts.

关键词： differential affine motion estimation optical-flow medical image registration multi-modality registration

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ON COSINE-MODULATED wavelet ORTHONORMAL BASES

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IEEE TRANSACTIONS ON image processing 1995年第2期4卷 162-176页

作者： GOPINATH, RA BURRUS, CS RICE UNIV INST COMP & INFORMAT TECHNOLDEPT ELECT & COMP ENGNHOUSTONTX 77251

Recently, multiplicity M, K-regular, orthonormal wavelet bases (that have implications in transform coding applications) have been constructed by several authors. This paper describes and parameterizes the cosine-modulated class of multiplicity M wavelet tight frames (WTF's). In these WTF's, the scaling function uniquely determines the wavelets. This is in contrast to the general multiplicity M case, where one has to, for any given application, design the scaling function and the wavelets, Several design techniques for the design of K regular cosine-modulated WTF's are described and their relative merits discussed. wavelets in K-regular WTF's may or may not be smooth, Since coding applications use WTFs with short length scaling and wavelet vectors (since long filters produce ringing artifacts, which is undesirable in, say, image coding), many smooth designs of K regular WTF's of short lengths are presented. In some cases, analytical formulas for the scaling and wavelet vectors are also given. In many applications, smoothness of the wavelets is more important than K regularity. We define smoothness of filter banks and WTF's using the concept of total variation and give several useful designs based on this smoothness criterion. Optimal design of cosine-modulated WTF's for signal representation is also described. All WTF's constructed in this paper are orthonormal bases, and we believe that this is always the case.

关键词： Filter bank image coding Transform coding wavelet analysis signal representations signal design signal processing signal analysis Speech coding Bit rate

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Adaptive Kalman filtering deconvolution via dyadic wavelet transform

Adaptive Kalman filtering deconvolution via dyadic wavelet t...

引用

Conference on wavelet applications in signal and image processing viii

作者： Dong, EQ Liu, GZ Zhang, ZP Xian Jiao Tong Univ Xian 710049 Peoples R China

ISBN: (纸本)0819437646

A new approach of adaptive Kalman filtering deconvolution (AKFD) is developed basing on dyadic wavelet transform. The technique discards the assumption of stationarity for signals in predictive deconvolution, and overcomes improving resolution at the price of decreasing signal-to-noise rate (SNR) obviously. The technique can well compress the reflection waveforms, but the noises are not variable in substance. So it has a better ability of resistance noise. Suppressing false reflections in dyadic wavelet transform domain is better than by applying AKFD in time domain. In addition the technique also has the characteristic of adaptive Kalman filtering in every band for a signal respectively, it enhances the adaptation of Kalman filtering, so the resolution is obvious higher than that one in time domain. A great deal of numerical models and real seismic data indicate that the technique has obvious effect. At the same time, the technique also overcomes the drawback of increasing the low-frequency component of AKFD in time domain. A great deal of numerical models and real seismic data indicate that the technique has obvious effect. The approach not only suits for seismic data, but also can be used for reference to another similar signal processing.

关键词： dyadic wavelet transform adaptive Kalman filtering deconvolution nonstationary signal

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Pseudo Power Signatures for image classification: SVD and projector approaches

Pseudo Power Signatures for image classification: SVD and pr...

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Conference on wavelet applications in signal and image processing viii

作者： Venkatachalam, V Rice Univ Dept Elect & Comp Engn Computat Math Lab Houston TX 77251 USA

ISBN: (纸本)0819437646

Segmentation and classification are important problems with applications in areas like textural analysis and pattern recognition. This paper describes a single-stage approach to solve the image segmentation/classification problem down to the pixel level, using energy density functions based on the wavelet transform. The energy density functions obtained, called Pseudo Power Signatures, are essentially functions of the scale and orientation, and are obtained using separable approximations to the 2-D wavelet transform. A significant advantage of these representations is that they are invariant to signal magnitude, and spatial location within the object of interest. Further, they lend themselves to fast and simple classification routines. We provide a complete formulation of the signature determination problem for 2-D, and propose an effective, albeit simple, technique based on a tensor singular value analysis, to solve the problem. We present an efficient computational algorithm, and a simulation result reflecting the strengths and limitations of this approach. We next present a detailed analysis of a more sophisticated method based on orthogonal projections to obtain signatures which are better representations of the underlying data.

关键词： segmentation classification wavelets CWT signatures

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