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A HYBRID wavelet-SPATIAL DENOISING FILTER

A HYBRID WAVELET-SPATIAL DENOISING FILTER

引用

18th International conference on Digital signal processing (DSP)

作者： Akl, Adib Yaacoub, Charles Holy Spirit Univ Kaslik Fac Engn Juniyah Lebanon

ISBN: (纸本)9781467358057

Noise is one of the most widespread problems present in nearly all imaging applications. The search for efficient image denoising methods is still a valid challenge. In spite of the sophistication of the recently proposed methods, most algorithms have not yet attained a desirable level of applicability. They all show an outstanding performance when the image model corresponds to the algorithm assumptions, but fail in general and create artifacts or remove fine image structures. Therefore, a universal "best" filter has yet to be found. wavelet analysis is a new method consisting of a set basis functions that can be used to analyze signals in both time (or space) and frequency domains simultaneously. In this paper, a novel hybrid filter for image despeckling that combines wavelet denoising and an enhanced adaptive Kuan filter is proposed, resulting in a significant gain with respect to many spatial as well as wavelet-based speckle reduction filters.

关键词： Despeckling DWT Kuan filter multiplicative noise thresholding

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Optimal Accuracy and Runtime Trade-Off in wavelet Based Single-Trial P300 Detection

Optimal Accuracy and Runtime Trade-Off in Wavelet Based Sing...

引用

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

作者： Motlagh, F. Tang, S. H. Motlagh, O. Univ Putra Malaysia Dept Mech & Mfg Engn Upm Serdang 43400 Selangore Malaysia UTeM Dept Robot & Automat Melaka 76100 Malaysia

ISBN: (纸本)9781479902699;9781479902675

Single-trail detection of P300 from EEG signals is the main challenge of diagnostic purposes and research applications. In this article, wavelet Transform is used for feature extraction from EEG signals. The goal is to prove the capability of wavelet transform in P300 feature extraction. A number of established wavelet feature extraction methods were evaluated from accuracy and computation speed perspectives. To conduct uniform evaluation, Support Vector Machine (SVM) was used for classification of all methods. The results show that DWT can be fast in computing signal features with lower accuracy, while a combination of DWT and T-CWT is proven to be more accurate when real-time computation is concerned.

关键词： EEG wavelet Transform Continues wavelet Transform discrete wavelet Transform Support Vector Machine

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Speckle Reduction for Ultrasound images Using Nonlinear Multi-Scale Complex wavelet Diffusion

Speckle Reduction for Ultrasound Images Using Nonlinear Mult...

引用

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

作者： Uddin, Muhammad Shahin Tahtali, Murat Lambert, Andrew J. Pickering, Mark R. Univ New S Wales Sch Engn & Informat Technol Canberra ACT Australia

ISBN: (纸本)9781479902699;9781479902675

Speckle noise is a major shortcoming of any type of ultrasound imaging. Hence, speckle reduction is vital in providing a better clinical diagnosis. The key objective of any speckle reduction algorithm is to attain a speckle free image, whilst preserving the important anatomical features. In this paper, we introduce a nonlinear multi-scale complex wavelet diffusion based algorithm for speckle reduction and sharp edge preservation of 2D ultrasound images. The proposed method exploits some useful features of the dual tree complex wavelet transform and nonlinear diffusion. Simulated experimental results demonstrate that our proposed algorithm significantly reduces speckle noise while preserving sharp edges without discernible distortions. The proposed approach performs better than the previous existing approaches in both qualitative and quantitative measures.

关键词： biomedical ultrasonics medical image processing speckle ultrasonic imaging wavelet transforms

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wavelet BASED CEPSTRAL COEFFICIENTS FOR NEURAL NETWORK SPEECH RECOGNITION

WAVELET BASED CEPSTRAL COEFFICIENTS FOR NEURAL NETWORK SPEEC...

引用

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

作者： Adam, T. B. Salam, M. S. Gunawan, T. S. Univ Teknol Malaysia Fac Comp Skudai Malaysia Intl Isla Univ Malaysia Dept Elect & Comp Engn Selangor Malaysia

ISBN: (纸本)9781479902699;9781479902675

Traditional cepstral analysis methods are often used as part of feature extraction process in speech recognition. However the cepstral analysis method uses the Discrete Fourier Transform (DFT) in one of its computation process. The DFT uses fixed frame resolution to analyze frames of signal thus it will result in an analysis that would not accurately analyze localized events. This paper investigates the use of the Discrete wavelet Transform (DWT) for calculating the cepstrum coefficients. Two wavelet types with different decomposition level are experimented to yield the cepstrum which is called the wavelet Cepstral Coefficient (WCC). To test the WCC speech recognizing task of recognizing 26 English alphabets were conducted. Under same number of feature dimension the WCC outperformed the MFCC with about 20% in terms of recognition rate under both speaker dependent and speaker independent task.

关键词： Speech recognition speech processing cepstral analysis wavelet transform feature extraction

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Experimental Approach On Thresholding Using Reverse Biorthogonal wavelet Decomposition For Eye image

Experimental Approach On Thresholding Using Reverse Biorthog...

引用

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

作者： Abidin, Zaheera Zainal Manaf, Mazani Shibhgatullah, Abdul Samad Univ Teknikal Malaysia Melaka UTeM Hang Tuah Jaya 76100 Melaka Malaysia Univ Teknol MARA Selangor 40450 Malaysia

ISBN: (纸本)9781479902699;9781479902675

This study focus on compression in wavelet decomposition for security in biometric data. The objectives of this research are two folds: a) to investigate whether compressed human eye image differ with the original eye and b) to obtain the compression ratio values using proposed methods. The experiments have been conducted to explore the application of sparsity-norm balance and sparsity-norm balance square root techniques in wavelet decomposition. The eye image with [320x280] dimension is used through the wavelet 2D tool of Matlab. The results showed that, the percentage of coefficients before compression energy was 99.65% and number of zeros were 97.99%. However, the percentage of energy was 99.97%, increased while the number of zeros was same after compression. Based on our findings, the impact of the compression produces different ratio and with minimal lost after the compression. The future work should imply in artificial intelligent area for protecting biometric data.

关键词： data compression iris recognition security of data wavelet transforms

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An Adaptive Threshold Method for Mass Detection in Mammographic images

An Adaptive Threshold Method for Mass Detection in Mammograp...

引用

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

作者： Eltoukhy, Mohamed Meselhy Faye, Ibrahima Univ Teknol PETRONAS CISIR Perak Malaysia

ISBN: (纸本)9781479902699;9781479902675

An early detection of abnormalities is the key point to improve the prognostic of breast Cancer. Masses are among the most frequent abnormalities. Their detection is however a very tedious and time-consuming task. This paper presents an automatic scheme to perform both detection and segmentation of breast masses. Firstly, the breast region is determined and extracted from the whole mammogram image. Secondly, an adaptive algorithm is proposed to perform an accurate identification of the mass region. Finally, a false positive reduction method is applied through a feature extraction method and classification using the advantages of multiresolution representations (curvelet and wavelet). The classification step is achieved using SVM and KNN classifiers to distinguish between normal and abnormal tissues. The proposed method is tested on 118 images from mammographic images analysis society (MIAS) datasets. The experimental results demonstrate that the proposed scheme achieves 100% sensitivity with average of 1.87 False Positive (FP) detections per image.

关键词： biological tissues cancer feature extraction image classification image representation image segmentation mammography medical image processing support vector machines wavelet transforms

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High Security image Steganography Using IWT and Graph Theory

High Security Image Steganography Using IWT and Graph Theory

引用

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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Biologically-inspired Video Enhancement Method For Robust Shape Recognition

Biologically-inspired Video Enhancement Method For Robust Sh...

引用

1st International conference on Communications, signal processing, and their applications (ICCSPA)

作者： Poursoltan, Saman Brinkworth, Russell Sorell, Matthew Univ Adelaide Adelaide SA 5005 Australia

ISBN: (纸本)9781467328210;9781467328203

The way image sequences are encoded by technological systems, that is video, is fundamentally tied to the way in which the human eye and brain interpret images and motion. This includes such aspects as resolution, colour, dynamic range, frame rates and spatial and temporal compression techniques. On the contrary, object identification algorithms are commonly based on single image analysis, such as the extraction of a single video frame from a sequence. This mismatch of, in particular, temporal processing paradigms means that most object analysis algorithms are not well suited to the data with which they are presented. In order to bridge this gap we investigate the temporal preconditioning of video data through a biologically-inspired vision model, based on multi-stage processing analogous to the vision systems of insects. In doing so, we argue that such an approach can lead to improved object identification through the enhancement of object perimeters and the amelioration of lighting and compression artefacts such as shadows and blockiness.

关键词： Shape Recognition Human Vision System video enhancement wavelet transform

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Analysis of Multispectral image Using Discrete wavelet Transform

Analysis of Multispectral Image Using Discrete Wavelet Trans...

引用

3rd International conference on Advanced Computing and Communication Technologies (ACCT)

作者： Singh, Hari Kumar Tomar, S. K. Singh, Pooja IETM JP Rohilkhand Univ Dept Elect & Commun Engn Bareilly Uttar Pradesh India RBMI Grp Inst Bareilly Uttar Pradesh India

ISBN: (纸本)9781467359658;9780769549415

In this paper we have analyzed the discrete wavelet transform of multispectral image of Bareilly region using MatLab tool. The wavelet transform is one of the most useful computational tools for a variety of signal and image processing applications. The wavelet transform is used for the compression of digital image because smaller data are important for storing images using less memory and for transmitting images faster and more reliably. wavelet transforms are useful for images to reduce unwanted noise and blurring. A discrete wavelet transform (DWT) is any wavelet transform for which the wavelets are discretely sampled. A key advantage it has over Fourier transforms is temporal resolution: it captures both frequency and time domain information.

关键词： wavelet wavelet Transform DWT Compression Techniques

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Noise Removal Using Double-Density Dual-Tree Complex DWT

Noise Removal Using Double-Density Dual-Tree Complex DWT

引用

IEEE 2nd International conference on image Information processing (ICIIP)

作者： Sarawale, Rahul K. Chougule, S. R. Bharati Vidyapeeths Coll Engg Dept Elect & Telecomm Kolhapur Maharashtra India Bharati Vidyapeeths Coll Engg Kolhapur Maharashtra India

ISBN: (纸本)9781467360999;9781467361002

The real world signals do not exist without noise. image denoising system should remove this noise to recover the original signal. Noise removal can be conducted in the time-space (original signal) domain or in a transform domain. To perform in transform domain, researchers utilize the Fourier Transform (FT) or the wavelet Transform (WT). The wavelet Transform, specifically Discrete wavelet Transform (DWT) performs well in noise removal applications. But they suffer from poor directional selectivity, shift sensitivity problem and absence of phase information. The proposed double-density dual-tree complex DWT is based on two scaling function and four distinct wavelets. This technique removes the demerits of the DWT and performs superior in image denoising applications than traditional linear processing (such as wiener filtering), stationary wavelet transform (SWT), dual-tree DWT, double-density DWT etc. In this paper, the prominent results in terms of PSNR, MSE and Histogram of the proposed system are compared with dual-tree complex wavelet transform and global thresholding method. From experimental point of view, the grayscale images are considered which are corrupted by Gaussian noise.

关键词： Complex wavelet transform double-density wavelet transform dual-tree complex wavelet transform

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