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Contrast Sensitivity of the wavelet, Dual Tree Complex wavelet, Curvelet, and Steerable Pyramid Transforms

IEEE TRANSACTIONS ON image processing 2016年第6期25卷 2739-2751页

作者： Hill, Paul Achim, Alin Al-Mualla, Mohammed E. Bull, David Univ Bristol Dept Elect & Elect Engn Bristol BS8 1UB Avon England Khalifa Univ Sci Technol & Res Abu Dhabi 127788 U Arab Emirates

Accurate estimation of the contrast sensitivity of the human visual system is crucial for perceptually based image processing in applications such as compression, fusion and denoising. Conventional contrast sensitivity functions (CSFs) have been obtained using fixed-sized Gabor functions. However, the basis functions of multiresolution decompositions such as wavelets often resemble Gabor functions but are of variable size and shape. Therefore to use the conventional CSFs in such cases is not appropriate. We have therefore conducted a set of psychophysical tests in order to obtain the CSF for a range of multiresolution transforms: the discrete wavelet transform, the steerable pyramid, the dual-tree complex wavelet transform, and the curvelet transform. These measures were obtained using contrast variation of each transforms' basis functions in a 2AFC experiment combined with an adapted version of the QUEST psychometric function method. The results enable future image processing applications that exploit these transforms such as signal fusion, superresolution processing, denoising and motion estimation, to be perceptually optimized in a principled fashion. The results are compared with an existing vision model (HDR-VDP2) and are used to show quantitative improvements within a denoising application compared with using conventional CSF values.

关键词： Discrete wavelet transforms contrast sensitivity function

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Source coding of wavelet-transformed digital HDTV for recording applications

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IEE PROCEEDINGS-VISION image AND signal processing 1996年第1期143卷 1-9页

作者： Vlachos, T BBC R&D Tadworth

A novel intraframe source-coding algorithm suitable for the recording of digital high-definition television signals is presented. A multilayered, hierarchical description of the source signal is obtained by means of a quad-tree, halfband wavelet transform. This transform decomposes the input signal into a collection of spectrally nonoverlapping sub-bands. These are used to influence the allocation of the available coding resources to the various layers, so that the integrity of visually significant features can be preserved. Individual sub-bands are quantised and entropy coded by using a predictive arithmetic coding technique. The algorithm is tuned to achieve bit-rate reduction ratios in the range 8:1 - 4:1 which is most useful for recording applications. Results obtained from simulating the coding algorithm show noticeable improvement over the current state-of-the-art international standard algorithm for still picture encoding, both in terms of subjective quality and of measured mean-square error.

关键词： intraframe coding image compression digital HDTV predictive arithmetic coding

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image denoising using neighbouring wavelet coefficients

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INTEGRATED COMPUTER-AIDED ENGINEERING 2005年第1期12卷 99-107页

作者： Chen, GY Bui, TD Krzyzak, A Concordia Univ Dept Comp Sci Montreal PQ H3G 1M8 Canada

The denoising of a natural image corrupted by Gaussian noise is a classical problem in signal or image processing. Donoho and his coworkers at Stanford pioneered a wavelet denoising scheme by thresholding the wavelet coefficients arising from the standard discrete wavelet transform. This work has been widely used in science and engineering applications. However, this denoising scheme tends to kill too many wavelet coefficients that might contain useful image information. In this paper. we propose one wavelet image thresholding scheme by incorporating neighbouring coefficients for both translation-invariant (TI) and non-TI cases. This approach is valid because a large wavelet coefficient will probably have large wavelet coefficients at its neighbour locations. Experimental results show that our algorithm is better than VisuShrink and the TI image denoising method developed by Yu et al. We also investigate different neighbourhood sizes and find that a size of 3 x 3 or 5 x 5 is the best among all window sizes.

关键词： image information wavelet coefficients image denoising method Noise reduction Neighbor image denoising Gaussian noise

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Index data embedding method utilizing quantitative relation of wavelet coefficients

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2001年第10期E84A卷 2508-2513页

作者： Iwata, M Shiozaki, A Univ Osaka Prefecture Grad Sch Engn Sakai Osaka 5998531 Japan

It is necessary condition for digital watermarking method for embedding memos or index data into digital photograph and so on that anyone can extract embedded data without specific keys or secret information. In this paper, we propose a data hiding technique for embedding index data into color images using wavelet transform. The proposed method keeps image quality and robustness against JPEG compression and general image processing using quantitative relation of wavelet coefficients.

关键词： wavelet transform digital watermark index data image signal

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An efficient compression scheme based on adaptive thresholding in wavelet domain using particle swarm optimization

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signal processing-image COMMUNICATION 2015年 32卷 33-39页

作者： Ahmadi, Kaveh Javaid, Ahmad Y. Salari, Ezzatollah Univ Toledo Dept EECS Toledo OH 43606 USA

image compression is one of the most important research areas in the field of image processing due to its large number of applications such as aerial surveillance, reconnaissance, medicine and multimedia communication. Even when high data rates are available, image compression is necessary in order to reduce the transmission cost. For applications involving information security, a fast delivery also reduces the chances of compromise over a communication channel. In this paper, we explore the possibility of using one of the computational intelligence techniques, namely, Particle Swarm Optimization (PSO), for optimal thresholding in the 2-D discrete wavelet transform (DWT) of an image. To this end, a set of optimal thresholds is obtained using the PSO algorithm. Finally, a variable length coding scheme, such as arithmetic coding is used to encode the results. Finding an optimal threshold value for the wavelet coefficients is very crucial in reducing the source entropy and bit-rate reduction. The proposed method is tested using several standard images against other popular techniques and proved to be more efficient compared to other methods. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Compression Adaptive thresholding Particle swarm optimization wavelet transform

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Complexity-constrained best-basis wavelet packet algorithm for image compression

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IEE PROCEEDINGS-VISION image AND signal processing 1998年第6期145卷 391-398页

作者： Marpe, D Cycon, HL Li, W Heinrich Hertz Inst Nachrichtentech Berlin GmbH D-10587 Berlin Germany Fachhsch Tech & Wirtschaft D-10315 Berlin Germany Old Dominion Univ Dept Math & Stat Norfolk VA 23529 USA

The concept of adapted waveform analysis using a best-basis selection out of a predefined library of wavelet packet (WP) bases allows an efficient image representation for the purpose of compression. image coding methods based on the best-basis WP representation have shown significant coding gains for some image classes compared with methods using a fixed dyadic structured wavelet basis, at the expense however, of considerably higher computational complexity. A modification of the best-basis method, the so-called complexity constrained best-basis algorithm (CCBB), is proposed which parameterises the complexity gap between the fast (standard) wavelet transform and the best wavelet packet basis of a maximal WP library. This new approach allows a 'suboptimal' best basis to be found with respect to a given budget of computational complexity or, in other words, it offers an instrument to control the trade-off between compression speed and coding efficiency. Experimental results are presented for image coding applications showing a highly nonlinear relationship between the rate-distortion (RD) performance and the computational complexity in such a way that a relatively small increase in complexity with respect to the standard wavelet basis results in a relatively high RD gain.

关键词： image compression coding wavelets

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Micro-movement magnification in video signals using complex wavelet analysis

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IET image processing 2017年第11期11卷 986-993页

作者： Fahmy, Gamal Fahmy, Mamdouh F. Fahmy, Omar M. Prince Sattam Bin Abdelaziz Univ Elect Engn Dept Kharj Saudi Arabia Assiut Univ Elect Engn Dept Assiut Egypt Future Univ FUE Elect Engn Dept New Cairo Egypt

Magnifying micro-movements from natural video has recently been investigated by several computer vision researchers, due to its impact in numerous applications. In this study, the authors analyse video signals and try to magnify micro-movements/vibrations to make them visible. These micro-movements are typically undetectable and cannot be seen by basic human vision. They utilise complex wavelets to analyse sequential frames and detect any minor change in object's spatial position. They magnify some specific complex wavelet frequency bands by a multiplication factor and reconstruct back the video signal after some manipulation and modification to make these micro-movements seen and observable. They compare their work with recent techniques in micro-motion magnification (Freeman et al.) and try to show the merits of each technique. These micro-movements can later be utilised in different applications such as medical imaging, structural engineering, mechanical engineering, physical feature analysis and industrial engineering, as will be seen in their experiments.

关键词： video signal processing image reconstruction image sequences wavelet transforms micromovement magnification video signals analysis complex wavelet analysis microvibration magnification sequential frame analysis multiplication factor video signal reconstruction medical imaging structural engineering mechanical engineering physical feature analysis industrial engineering

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Lifting scheme of biorthogonal wavelet transform based on discrete interpolatory splines

Lifting scheme of biorthogonal wavelet transform based on di...

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Conference on wavelet applications in signal and image processing viii

作者： Averbuch, AZ Pevnyi, AB Zheludev, VA Tel Aviv Univ Dept Comp Sci IL-69978 Tel Aviv Israel

ISBN: (纸本)0819437646

In the paper we present a new family of biorthogonal wavelet transforms and a related library of biorthogonal periodic symmetric waveforms. For the construction we used the interpolatory discrete splines which enabled us to design a library of perfect reconstruction filter banks. These filter banks are related to Butterworth filters. The construction is performed in a "lifting" manner. The difference from the conventional lifting scheme is that all the transforms are implemented in the frequency domain with the use of the fast Fourier transform (FFT). Two ways to choose the control filters are suggested. The proposed scheme is based on interpolation and, as such, it involves only samples of signals and it does not require any use of quadrature formulas. These filters have linear phase property and the basic waveforms are symmetric. In addition, these filters yield perfect frequency resolution.

关键词： discrete splines biorthogonal wavelets lifting scheme Butterworth filters

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Low-bit-rate coding of underwater video using wavelet-based compression algorithms

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IEEE JOURNAL OF OCEANIC ENGINEERING 1997年第2期22卷 393-400页

作者： Hoag, DF Ingle, VK Gaudette, RJ Department of Electrical and Computer Engineering Northeastern University Boston MA USA

Recent advances in autonomous underwater vehicle (AUV) and underwater communication technology have promoted a surge of research activity within the area of signal and information processing. A new application is proposed herein for capturing and processing underwater video onboard an untethered AW, then transmitting it to a remote platform using acoustic telemetry. Since video communication requires a considerably larger bandwidth than that provided by an underwater acoustic channel, the data must be massively compressed prior to transmission from the AUV. Past research has shown that the low contrast and low-detailed nature of underwater imagery allows for low-bit-rate coding of the data by wavelet-based image-coding algorithms. In this work, these findings have been extended to the design of a wavelet-based hybrid video encoder which employs entropy-constrained vector quantization (ECVQ) with overlapped block-based motion compensation. The ECVQ codebooks were designed from a statistical source model which describes the distribution of high subband wavelet coefficients in both intraframe and prediction error images. Results indicate that good visual quality can be achieved for very low bit-rate coding of underwater video with our algorithm.

关键词： Video compression Underwater communication Underwater acoustics image coding Underwater vehicles Communications technology Surges signal processing Information processing Acoustic applications

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A comparative study of wavelet families for classification of wrist motions

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COMPUTERS & ELECTRICAL ENGINEERING 2012年第6期38卷 1798-1807页

作者： Hariharan, M. Fook, C. Y. Sindhu, R. Ilias, Bukhari Yaacob, Sazali Univ Malaysia Perlis Sch Mechatron Engn Perlis Malaysia Univ Malaysia Perlis Sch Microelect Engn Perlis Malaysia

The selection of most suitable mother wavelet function is still an open research problem in various signal and image processing applications. This paper presents a comparative study of different wavelet families (Daubechies, Symlets, Coiflets, and Biorthogonal) for analysis of wrist motions from electromyography (EMG) signals. EMG signals are decomposed into three levels using discrete wavelet packet transform. From the decomposed EMG signals, root mean square (RMS) value, autoregressive (AR) model coefficients (4th order) and waveform length (WL) are extracted. Two data projection methods such as principal component analysis (PCA) and linear disciminant analysis (LDA) are used to reduce the dimensionality of the extracted features. Probabilistic neural network (PNN) and general regression neural network (GRNN) are employed to classify the different types of wrist motions, which gives a promising accuracy of above 99%. From the analysis, we inferred that 'Biorthogonal' and 'Coiflets' wavelet families are more suitable for accurate classification of EMG signals of different wrist motions. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： signal processing COMPARATIVE studies waveletS (Mathematics) CLASSIFICATION image processing APPLICATION software ELECTROMYOGRAPHY PRINCIPAL components analysis

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