Conferences related to Wavelet coefficients

Back to Top

2023 Annual International Conference of the IEEE Engineering in Medicine & Biology Conference (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.


IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium

All fields of satellite, airborne and ground remote sensing.


2020 59th IEEE Conference on Decision and Control (CDC)

The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.



Periodicals related to Wavelet coefficients

Back to Top

Automation Science and Engineering, IEEE Transactions on

The IEEE Transactions on Automation Sciences and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. We welcome results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, ...


Biomedical Circuits and Systems, IEEE Transactions on

The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Broadcasting, IEEE Transactions on

Broadcast technology, including devices, equipment, techniques, and systems related to broadcast technology, including the production, distribution, transmission, and propagation aspects.


Circuits and Systems for Video Technology, IEEE Transactions on

Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...



Most published Xplore authors for Wavelet coefficients

Back to Top

Xplore Articles related to Wavelet coefficients

Back to Top

Block biorthogonal channel coding using wavelets

MILCOM 92 Conference Record, 1992

The authors introduce block biorthogonal coding using wavelets, a channel coding method that uses the unique orthogonality properties of wavelet coefficient matrices (WCM) to efficiently encode information bits. The benefit of this algorithm is its diversity-based coding gains in fading and burst noise channels. The authors compare wavelet-Hadamard codes, which are obtained from wavelet-Hadamard matrices, a class of wavelet coefficient ...


Contrast enhancement mammograms using denoising in wavelet coefficients

The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE), 2013

Contrast enhancement in x-ray mammograms is important in improvement of radiologists' reading and interpretation. In many cases, it is difficult to discern signs of breast cancer because mammograms are low contrast and very noisy. This paper proposes improved contrast enhancement method in mammograms using denoising in wavelet coefficients. First, mammograms are decomposed by wavelet transform. Second, the ratio between approximate ...


Wavelet Based Image Denoising Using Adaptive Thresholding

International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007), 2007

The denoising of a natural image corrupted by Gaussian noise is a long established problem in signal or image processing. Even though much work has been done in the field of wavelet thresholding, most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds. This paper describes a new method for suppression of noise ...


Semi-fragile watermarking for image content authentication

Proceedings 7th International Conference on Signal Processing, 2004. Proceedings. ICSP '04. 2004., 2004

In this paper, we propose a quantization-based semi-fragile watermarking algorithm for content authentication. The watermark can be blindly extracted. The formulation of judge threshold is given from the point of probability theory. The tempered areas of watermarked image can be distinguished by the predefined threshold. Our scheme is robust to incidental manipulations while fragile to malicious distortions, and can distinguish ...


Context-based multiscale classification of document images using wavelet coefficient distributions

IEEE Transactions on Image Processing, 2000

In this paper, an algorithm is developed for segmenting document images into four classes: background, photograph, text, and graph. Features used for classification are based on the distribution patterns of wavelet coefficients in high frequency bands. Two important attributes of the algorithm are its multiscale nature-it classifies an image at different resolutions adaptively, enabling accurate classification at class boundaries as ...



Educational Resources on Wavelet coefficients

Back to Top

IEEE-USA E-Books

  • Block biorthogonal channel coding using wavelets

    The authors introduce block biorthogonal coding using wavelets, a channel coding method that uses the unique orthogonality properties of wavelet coefficient matrices (WCM) to efficiently encode information bits. The benefit of this algorithm is its diversity-based coding gains in fading and burst noise channels. The authors compare wavelet-Hadamard codes, which are obtained from wavelet-Hadamard matrices, a class of wavelet coefficient matrices, with traditional Hadamard codes and find them to be equivalent to additive white Gaussian noise and superior in fading and burst noise channels.<<ETX>>

  • Contrast enhancement mammograms using denoising in wavelet coefficients

    Contrast enhancement in x-ray mammograms is important in improvement of radiologists' reading and interpretation. In many cases, it is difficult to discern signs of breast cancer because mammograms are low contrast and very noisy. This paper proposes improved contrast enhancement method in mammograms using denoising in wavelet coefficients. First, mammograms are decomposed by wavelet transform. Second, the ratio between approximate subband and detail subband as signal-to-noise ratio is computed. Finally, detail subbands which have the ratio lower than the criteria are boosted to improve mammograms contrast while detail subbands having the ratio higher than the criteria are set to zero for noise suppression in the same time. Contrast measure and peak- signalto-noise ratio are used to evaluate the performance of the proposed method. The experimental results show higher contrast 17.05% than the conventional method while a bit different in peak-signal-to-noise ratio.

  • Wavelet Based Image Denoising Using Adaptive Thresholding

    The denoising of a natural image corrupted by Gaussian noise is a long established problem in signal or image processing. Even though much work has been done in the field of wavelet thresholding, most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds. This paper describes a new method for suppression of noise in image by fusing the wavelet denoising technique with optimized thresholding function, improving the denoised results significantly. Simulated noise images are used to evaluate the denoising performance of proposed algorithm along with another wavelet-based denoising algorithm. Experimental result shows that the proposed denoising method outperforms standard wavelet denoising techniques in terms of the PSNR and the preservation of edge information. We have compared this with various denoising methods like Wiener filter, Visu shrink, Oracle shrink and Bayes shrink.

  • Semi-fragile watermarking for image content authentication

    In this paper, we propose a quantization-based semi-fragile watermarking algorithm for content authentication. The watermark can be blindly extracted. The formulation of judge threshold is given from the point of probability theory. The tempered areas of watermarked image can be distinguished by the predefined threshold. Our scheme is robust to incidental manipulations while fragile to malicious distortions, and can distinguish the distortions caused by great incidental processing with the malicious tempering. The advantage of our scheme is compared with other algorithms in the last.

  • Context-based multiscale classification of document images using wavelet coefficient distributions

    In this paper, an algorithm is developed for segmenting document images into four classes: background, photograph, text, and graph. Features used for classification are based on the distribution patterns of wavelet coefficients in high frequency bands. Two important attributes of the algorithm are its multiscale nature-it classifies an image at different resolutions adaptively, enabling accurate classification at class boundaries as well as fast classification overall-and its use of accumulated context information for improving classification accuracy.

  • Denoising of hepatic signals with Partial Cycle Spinning

    Partial Cycle Spinning (PCS) is a technique that allows denoising of signals with lower complexity than Cycle Spinning (CS). PCS is a simplified version of CS, in which only a subset of the shifts used in CS is used. The results obtained with PCS show some variability depending on the shifts chosen. The quality of the processed signals can be improved by taking advantage of this variability. This paper presents a study of the influence of the choice of shifts on the PCS algorithm for medical signal denoising applications, to be more precise for hepatic signals of ultrasonic origin. The results obtained, both for synthetic signals and ultrasonic hepatic signals, show how the choice of shifts in the PCS algorithm influences the quality of the final processed signal.

  • Statistical image restoration based on adaptive wavelet models

    We propose image restoration algorithms based on adaptive wavelet-domain statistical models. We present a method to estimate the model parameters from the observations, and solve the restoration problem in orthonormal and translation-invariant wavelet domains. Substantial improvements over previous wavelet-based restoration methods are obtained. The use of a translation- invariant basis further enhances the restoration performance.

  • A new wavelet-based method for despeckling SAR images

    In this paper, a wavelet-based despeckling method is proposed for suppressing speckle noise in synthetic aperture radar (SAR) images. A new threshold is proposed to classify the wavelet coefficients into significant and insignificant ones. Local statistic in the wavelet domain is used to further classify the significant coefficients into the edge and non-edge coefficients. The edge coefficients remain unaltered, whereas the non-edge and the insignificant ones are reduced in magnitude. Experiments are carried out on a noise-free image corrupted with simulated speckle noise, and a real SAR image. The results show that the proposed method provides a performance better than that of other methods in terms of the peak signal-to-noise ratio and ability to suppress speckle in the homogeneous areas. In addition, it introduces a bias that is much smaller than that of the other methods as well as preserves edges quite well.

  • Blind Image Watermarking Technique for Digital Phone Camera

    In today's modern world, digital phone cameras are common daily gadgets that most people have and use. In the event of a traffic accident, a fire accident, or a criminal act, anyone will be able to capture these important moments and use authentic photographs for evidence purposes. Digital watermarking is able to ensure that the digital photographs taken are authentic and indeed taken from a particular phone camera. This paper presents a blind image watermarking technique for digital phone camera. This method is based on singular value decomposition (SVD) and wavelet decomposition. Experimental results show that the proposed technique performs well in security and robustness against JPEG compression.

  • Scanned maps processing using wavelet domain hidden Markov models

    This paper seeks to find ways to remove the unwanted information from the scanned GIS maps using wavelet domain hidden Markov models. WHMMs have proven to be a valuable tool for signal denoising, while they preserve the edges, so they can be used to remove the dithering effect that occurs during the printing process of the map. Linework data can be viewed as edges in the scanned map image. And, since WHMMs are well suited to images containing singularities (edges), they provide a good classifier for distinguishing between linework and elevation data (smoother areas in the image).



Standards related to Wavelet coefficients

Back to Top

No standards are currently tagged "Wavelet coefficients"