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image denoising algorithm based on hybrid neighborhood filter

Image denoising algorithm based on hybrid neighborhood filte...

引用

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

作者： Sabahaldin A. Hussain Sami M. Gorashi Electrical and Electronic Engineering Department OIU Sudan

image denoising is an active area of research and probably one of the most studied problems in the image processing fields. In this paper we describe a new hybrid image denoising algorithm which combines Gaussian based neighborhood spatial filter with wavelet transform that based on neighborhood thresholding function which takes the correlation of the magnitude of the wavelet coefficient with its neighbors into consideration to decide whether the coefficient is noisy or noise free. Accordingly, noises are detected with the help of the surrounding information and are removed. Experimental results show that the proposed algorithm can effectively remove the image noises with less processing time as compared with the state-of-the-art denoising algorithm.

关键词： Noise reduction Noise Noise measurement Algorithm design and analysis Filtering algorithms wavelet analysis wavelet transforms

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Medical image watermarking based on DWT and ICA for copyright protection 1

引用

36th National Systems conference on Recent Advancements in System Modelling applications, NSC 2012

作者： Mangaiyarkarasi, P. Arulselvi, S. Department of Electronics and Instrumentation Engineering Annamalai University Chidambaram TamilNadu India

ISBN: (数字)9788132210351

ISBN: (纸本)9788132210344

Digital watermarking has been proposed to increase medical image security, confidentiality and integrity. Medical image watermarking is a special subcategory of image watermarking in the sense that the images have special requirements. Particularly, watermarked medical images should not differ perceptually from their original counterparts, because the clinical reading of the images for diagnosis must not be affected. Hence, in this paper, a robust and imperceptible watermarking technique based on discrete wavelet transform (DWT) is proposed for medical images. For extraction, a blind source separation technique, namely, independent component analysis is attempted. Conventional extraction techniques need embedding parameters such as strength, location and information about watermark or original image, whereas, ICA extracts the watermark without the use of these parameters. The quality of watermarked image and extracted watermark are measured in terms of peak signal to noise ratio (PSNR) and normalized correlation (NC) values respectively. Robustness of the proposed scheme is validated against various image processing attacks. The proposed work is attempted on color images also. A true color image is split into red, green and blue components, where watermark is embedded in each plane individually followed by extraction. Performance of the proposed scheme is compared among the color components, and it is recommended that blue plane is the better choice of embedding watermark for medical color images. © 2013 Springer.

关键词： Discrete wavelet transforms

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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

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

作者： F. Motlagh S.H. Tang O. Motlagh Department of Mechanical & Manufacturing Engineering Universiti Putra Malaysia Selangore Malaysia Department of Robotics and Automation Universiti Teknikal Malaysia Melaka (UTeM) Melaka Malaysia

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： Continuous wavelet transforms Discrete wavelet transforms Electroencephalography Oscillators

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Multi-resolution Shape Analysis via Non-Euclidean wavelets: applications to Mesh Segmentation and Surface Alignment Problems

Multi-resolution Shape Analysis via Non-Euclidean Wavelets: ...

引用

26th IEEE conference on Computer Vision and Pattern Recognition (CVPR)

作者： Kim, Won Hwa Chung, Moo K. Singh, Vikas Univ Wisconsin Dept Comp Sci 1210 W Dayton St Madison WI 53706 USA Univ Wisconsin Dept Biostat & Med Informat Madison WI USA

ISBN: (纸本)9780769549897

The analysis of 3-D shape meshes is a fundamental problem in computer vision, graphics, and medical imaging. Frequently, the needs of the application require that our analysis take a multi-resolution view of the shape's local and global topology, and that the solution is consistent across multiple scales. Unfortunately, the preferred mathematical construct which offers this behavior in classical image/signal processing, wavelets, is no longer applicable in this general setting (data with non-uniform topology). In particular, the traditional definition does not allow writing out an expansion for graphs that do not correspond to the uniformly sampled lattice (e.g., images). In this paper, we adapt recent results in harmonic analysis, to derive Non-Euclidean wavelets based algorithms for a range of shape analysis problems in vision and medical imaging. We show how descriptors derived from the dual domain representation offer native multi-resolution behavior for characterizing local/global topology around vertices. With only minor modifications, the framework yields a method for extracting interest/key points from shapes, a surprisingly simple algorithm for 3-D shape segmentation (competitive with state of the art), and a method for surface alignment (without landmarks). We give an extensive set of comparison results on a large shape segmentation benchmark and derive a uniqueness theorem for the surface alignment problem.

关键词： computer vision feature extraction image representation image resolution image segmentation mesh generation wavelet transforms

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wavelet based Cepstral Coefficients for neural network speech recognition

Wavelet based Cepstral Coefficients for neural network speec...

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

作者： T. B. Adam M.S. Salam T.S. Gunawan Universiti Teknologi Malaysia Malaysia Department of Electrical and Computer Engineering International Islamic University Malaysia Malaysia

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 Abstracts Discrete wavelet transforms Mel frequency cepstral coefficient Markov processes

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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

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

作者： Zaheera Zainal Abidin Mazani Manaf Abdul Samad Shibhgatullah Universiti Teknikal Malaysia Melaka (UTeM) Melaka Malaysia Universiti Teknologi MARA (UITM) Shah Alam Selangor Malaysia

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： MATLAB Ear Three-dimensional displays Biomedical imaging Cryptography

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wavelet based image fusion techniques

Wavelet based image fusion techniques

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International conference on Intelligent Systems and signal processing (ISSP)

作者： P. Mirajkar Pradnya D. Ruikar Sachin Electronics & Telecommunication Dept. ADCET Ashta Researcher E&Tc Dept. Sinhgad Acadmy of Engg. Pune Electronics & Telecommunication Dept. Sinhgad Acadmy of Engg. Pune

The fusion of images is the process of combining two or more images into a single image retaining important features from each. Fusion is an important technique within many disparate fields such as remote sensing, robotics and medical applications. The result of image fusion is a single image which is more suitable for human and machine perception or further image-processing tasks. The image fusion algorithm based on wavelet transform is proposed to prove the geometric resolution of the images, in which two images to be processed are firstly decomposed into sub images and then the information is performed using these images under the certain criteria and finally these sub images are reconstructed into result image with plentiful information. In this paper three different image fusion methods based wavelet transform are implemented. And the results are compared and best method is found.

关键词： image fusion Discrete wavelet transforms wavelet analysis image resolution signal to noise ratio

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Improved single image super-resolution using sparsity and structured dictionary learning in wavelet domain

Improved single image super-resolution using sparsity and st...

引用

IEEE signal processing and Communications applications (SIU)

作者： Mahmoud Nazzal Huseyin Ozkaramanli Electrical and Electronic Engineering Deaprtment Eastern Mediterranean University Turkey

This paper introduces a single-image superresolution approach which is based on sparse representation over dictionaries learned in the wavelet domain. The diagonal detail subband learning and reconstruction is improved by designing two diagonal dictionaries; one for the diagonal and another for the anti-diagonal orientations. Four pairs (low resolution and high resolution) of subband dictionaries are designed. The sparse representation coefficients for the respective low and high resolution images are assumed to be the same. The proposed algorithm is compared with the leading super-resolution techniques and is shown to excel both visually and quantitatively, with an average PSNR raise of 0.82 dB over the Kodak set. Moreover, this algorithm is shown to significantly reduce the dictionary learning computational complexity by designing compactly sized structural dictionaries.

关键词： Dictionaries image resolution image reconstruction signal resolution Discrete wavelet transforms PSNR Training

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Analyzing subcellular structure with optical Fourier filtering based on Gabor filters

Analyzing subcellular structure with optical Fourier filteri...

引用

conference on Biomedical applications of Light Scattering vii

作者： Boustany, Nada N. Sierra, Heidy Rutgers State Univ Dept Biomed Engn Piscataway NJ 08854 USA

ISBN: (纸本)9780819493613

Label-free measurement of subcellular morphology can be used to track dynamically cellular function under various conditions and has important applications in cellular monitoring and in vitro cell assays. We show that optical filtering of scattered light by two-dimensional Gabor filters allows for direct and highly sensitive measurement of sample structure. The Gabor filters, which are defined by their spatial frequency, orientation and Gaussian envelope, can be used to track locally and in situ the characteristic size and orientation of structures within the sample. Our method consists of sequentially implementing a set of Gabor filters via a spatial light modulator placed in a conjugate Fourier plane during optical imaging and identifying the filters that yield maximum signal. Using this setup, we show that Gabor filtering of light forward-scattered by spheres yields an optical response which varies linearly with diameter between 100nm and 2000nm. The optical filtering sensitivity to changes in diameter is on the order of 20nm and can be achieved at low image resolution. We use numerical simulations to demonstrate that this linear response can be predicted from scatter theory and does not vary significantly with changes in refractive index ratio. By applying this Fourier filtering method in samples consisting of diatoms and cells, we generate false-color images of the object that encode at each pixel the size of the local structures within the object. The resolution of these encoded size maps in on the order of 0.36 mu m. The pixel histograms of these encoded images directly provide 20nm resolved "size spectra", depicting the size distribution of structures within the analyzed object. We use these size spectra to differentiate the morphology of apoptosis-competent and bax/bak null apoptosis-resistant cells during cell death. We also utilize the sensitivity of the Gabor filters to object orientation to track changes in organelle morphology, and detect mitochondrial

关键词： Light scattering optical processing cell analysis subcellular structure and dynamics apoptosis

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

作者： V Thanikaiselvan P Arulmozhivarman School of Electronics Engineering VIT University Vellore Tamilnadu India

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： Hafnium Robustness

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