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A Framework for wavelet-Based Analysis and processing of Color Filter Array images with applications to Denoising and Demosaicing

A Framework for wavelet-Based Analysis and Processing of Col...

引用

International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Keigo Hirakawa Xiao-Li Meng Patrick J. Wolfe Department of Statistics Harvard University Cambridge MA USA

This paper presents a new approach to demosaicing of spatially sampled image data observed through a color filter array, in which properties of Smith-Barnwell filterbanks are employed to exploit the correlation of color components in order to reconstruct a subsampled image. The method is shown to be amenable to wavelet-domain denoising prior to demosaicing, and a general framework for applying existing image denoising algorithms to color filter array data is also described. Results indicate that the proposed method performs on a par with the state of the art for far lower computational cost, and provides a versatile, effective, and low-complexity solution to the problem of interpolating color filter array data observed in noise.

关键词： image color analysis wavelet analysis image analysis Filters Noise reduction Colored noise image denoising Frequency image reconstruction Pixel

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Peak Transform - A Nonlinear Transform for Efficient image Representation and Coding

Peak Transform - A Nonlinear Transform for Efficient Image R...

引用

IEEE International conference on image processing

作者： Zhihai He Department of Electrical and Computer Engineering University of Missouri Columbia MO USA

In this work, we introduce a nonlinear geometric transform, called peak transform, for efficient image representation and coding. Coupled with wavelet transform and subband decomposition, the peak transform is able to significantly reduce signal energy in high-frequency subbands and achieve a significant transform coding gain. This has important applications in efficient data representation and compression. Based on peak transform (PT), we design an image encoder, called PT encoder, for efficient image compression. Our extensive experimental results demonstrate that, in wavelet-based subband decomposition, the signal energy in high-frequency subbands can be reduced by up to 60% if a peak transform is applied. The PT image encoder outperforms state-of-the-art JPEG2000 and H.264 (INTRA) encoders by up to 2-3 dB in PSNR (peak signal-to-noise ratio), especially for images with a significant amount of high-frequency components.

关键词： image representation image coding wavelet transforms Discrete wavelet transforms Transform coding Discrete cosine transforms Karhunen-Loeve transforms PSNR Discrete transforms Videos

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Blind image Watermarking Scheme in DWT-SVD Domain

Blind Image Watermarking Scheme in DWT-SVD Domain

引用

International conference on Intelligent Information Hiding and Multimedia signal processing (IIHMSP)

作者： Kyung-Su Kim Min-Jeong Lee Heung-Kyu Lee Department of EECS Korea Advanced Institute of Science and Technology Daejeon South Korea

Discrete wavelet Transform (DWT) is widely applied to image watermarking applications because it decomposes a cover image into spatial domain as well as frequency domain simultaneously. Also, Singular Value Decomposition (SVD) is suitable for watermarking applications since some largest singular values are sufficient to embed watermarks instead of using all singular values. We propose a hybrid blind watermarking scheme based on DWT and SVD for image data. The proposed scheme embeds watermarks by modifying log-scaled singular value of selected coefficients of all sub-bands. We have found two properties to be robust against malicious attacks commonly happened to images. We performed experiments to prove that the proposed scheme has the robustness against to a wide range of attacks such as JPEG compression, Gaussian noise addition, median filtering, blurring, histogram equalization, gamma correction, reseating, shift, and rotation.

关键词： Watermarking Discrete wavelet transforms Noise robustness wavelet domain Frequency domain analysis Singular value decomposition Transform coding image coding Gaussian noise Filtering

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Multi-Dimensional Biomedical image De-Noising using Haar Transform

Multi-Dimensional Biomedical Image De-Noising using Haar Tra...

引用

International conference on Digital signal processing (DSP)

作者： Eva Hostalkova Oldrich Vysata Ales Prochazka Department of Computing and Control Engineering Institute of Chemical Technology in Prague Prague Czech Republic

image de-noising and enhancement form two fundamental problems in many engineering and biomedical applications. The paper is devoted to the study of the multi-resolution approach to this topic employing the Haar wavelet transform and its application to processing of volumetric magnetic resonance image sets corrupted with additional noise. The resulting coefficients are thresholded and exploited for subsequent reconstruction. The Haar transform is evaluated using both the two-dimensional approach applied individually to each image layer, and the three-dimensional technique performed on the image volume as a whole. In noise reduction, the latter approach profits from similarities between the neighbouring image layers and shows a considerable improvement over the former method. Results are presented in numerical and graphical forms using three-dimensional visualization tools.

关键词： Biomedical imaging Noise reduction image denoising Biomedical engineering wavelet transforms Magnetic resonance Magnetic noise image reconstruction Performance evaluation Visualization

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Improved Adaptive Lifting Scheme for wavelet-Based image Compression

Improved Adaptive Lifting Scheme for Wavelet-Based Image Com...

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International conference on Intelligent Information Hiding and Multimedia signal processing (IIHMSP)

作者： Qiong Li Guo-Qiang Li Yi-Liang He Xia-Mu Niu School of Electrical Engineering Harbin Institute of Technology Harbin China Department of Mathematics Harbin Institute of Technology Harbin China

ISBN: (纸本)9780769529943;0769529941

This paper investigates an adaptive lifting scheme for wavelet-based image compression, which performs update before prediction, and then we proposes an improved adaptive update and prediction scheme to better exploit the correlation among neighboring pixels. Simulation results show that the proposed scheme generates in the transformed domain lower coefficients' entropy, lower high-frequency coefficients' energy and more zero values, which make it useful for image compression applications.

关键词： image coding Frequency Pixel Adaptive filters Entropy image reconstruction Helium Mathematics Error analysis Quantization

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Lung Segmentation in Pulmonary CT images using wavelet Transform

Lung Segmentation in Pulmonary CT Images using Wavelet Trans...

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Omid Talakoub Javad Alirezaie Paul Babyn Department of Electrical and Computer Engineering Ryerson University Canada Department of Systems Design Engineering University of Waterloo Canada Department of Medical Imaging University of Toronto Canada

Computer-aided diagnosis (CAD) has become a major research interest in diagnostic radiology and medical imaging. The basic goal of CAD is to provide a computer output as a second opinion to assist medical image interpretation by improving accuracy, consistency of diagnosis, and image interpretation time. Since a CAD system is only interested in analyzing a specific organ, segmentation of computer tomography (CT) images is a precursor to most image analysis applications. A fully automated method is presented to segment lung in pulmonary CT images based on detected lung edges by wavelet analysis. Due to wavelet transformation characteristics, the proposed method is not only computational inexpensive compared to other existing methods such as snakes or watershed, but also is robust and accurate in detecting lung borders. A set of 330 low dose (50 mA) CT images were processed demonstrating accuracy and satisfactory performance of the algorithm.

关键词： Lungs image segmentation Computed tomography wavelet transforms image edge detection Biomedical imaging image analysis Computer aided diagnosis Radiology Medical diagnostic imaging

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Change detection in urban scenes by fusion of SAR and hyperspectral data

Change detection in urban scenes by fusion of SAR and hypers...

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conference on Remote Sensing for Environmental Monitoring, GIS applications, and Geol viil

作者： Borghys, Dirk Shimoni, Michal Perneel, Christlaan Royal Mil Acad Signal & Image Ctr Renaissancelaan 30 B-1000 Brussels Belgium Royal Mil Acad Dept Math Appl Renaissancelaan 30 B-1000 Brussels Belgium

ISBN: (纸本)9780819469076

Urban areas are rapidly changing all over the world and therefore provoke the necessity to update urban maps frequently. Remote sensing has been used for many years to monitor these changes. The urban scene is characterized by a very high complexity, containing objects formed from different types of man-made materials as well as natural vegetation. Hyperspectral sensors provide the capability to map the surface materials present in the scene using their spectra and therefore to identify the main object classes in the scene in a relatively easy manner. However ambiguities persist where different types of objects are constructed of the same material. This is for instance the case for roads and roof covers. Although higher-level image processing (e.g. spatial reasoning) might be able to relief some of these constraints, this task is far from straight forward. In the current paper the authors fused information gathered using a hyperspectral sensor with that of high-resolution polarimetric SAR data. SAR data give information about the type of scattering backscatter from an object in the scene, its geometry and its dielectric properties. Therefore, the information obtained using the SAR processing is complementary to that obtained using hyperspectral data. This research was applied on a dataset consisting of hyperspectral data from the HyMAP sensor (126 channels in VIS-SWIR) and E-SAR data which consists of full-polarimetric L-band and dual-polarisation (HH and VV) X-band data. Two supervised classifications are used;'Logistic Regression' (LR) which applied to the SAR and the PoISAR data and a 'Matched Filter' which is applied to the hyperspectral data. The results of the classification are fused in order to improve the mapping of the main classes in the scene and were compared to a ground truth map that was constructed by combining a digital topographic map and a vectorized cadastral map of the research area. An adequate change detection of man-made objects in urban scen

关键词： change detection hyperspectral SAR PoISAR logistic regression urban mapping

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Registration of 2D to 3D joint images using phase-based mutual information

Registration of 2D to 3D joint images using phase-based mutu...

引用

Medical Imaging 2007 conference

作者： Dalvia, Rupin Abugharbieh, Rafeef Pickering, Mark Scarvell, Jennie Smith, Paul Univ British Columbia Biomed Signal & Image Comp Lab Vancouver BC V5Z 1M9 Canada Australian Def Force Acad Sch Info Tech & Elect Engn Canberra ACT Australia Univ Canberra Sch Hlth Sci Canberra ACT Australia Canberra Hosp Trauma & Orthopaed Res Unit Canberra ACT Australia

ISBN: (纸本)9780819466303

Registration of two dimensional to three dimensional orthopaedic medical image data has important applications particularly in the area of image guided surgery and sports medicine. Fluoroscopy to computer tomography (CT) registration is an important case, wherein digitally reconstructed radiographs derived from the CT data are registered to the fluoroscopy data. Traditional registration metrics such as intensity-based mutual information (MI) typically work well but often suffer from gross misregistration errors when the image to be registered contains a partial view of the anatomy visible in the target image. Phase-based MI provides a robust alternative similarity measure which, in addition to possessing the general robustness and noise immunity that MI provides, also employs local phase information in the registration process which makes it less susceptible to the aforementioned errors. In this paper, we propose using the complex wavelet transform for computing image phase information and incorporating that into a phase-based MI measure for image registration. Tests on a CT volume and 6 fluoroscopy images of the knee are presented. The femur and the tibia in the CT volume were individually registered to the fluoroscopy images using intensity-based MI, gradient-based MI and phase-based MI. Errors in the coordinates of fiducials present in the bone structures were used to assess the accuracy of the different registration schemes. Quantitative results demonstrate that the performance of intensity-based MI was the worst. Gradient-based MI performed slightly better, while phase-based MI results were the best consistently producing the lowest errors.

关键词： registration multiresolution and wavelets other (2D-3D registration)

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Multi-focus image Fusion Algorithm Based on Regional Firing Characteristic of Pulse Coupled Neural Networks

Multi-focus Image Fusion Algorithm Based on Regional Firing ...

引用

International conference on Bio-Inspired Computing: Theories and applications, BICTA

作者： Xiaobo Qu Jingwen Yan Department of Communication Engineering Xiamen University Xiamen China Key Laboratory of Digital Signal and Image Processing of Guangdong Province Shantou University Shantou China

Multi-focus image fusion aims at overcoming imaging cameras' finite depth of field by combining information from multiple images with the same scene. In this paper, a regional firing intensity (RFI) is defined, which is based on the statistical characteristic in local window of neuron firing times when pulse coupled neural networks (PCNN) is utilized in the image fusion. A novel image fusion algorithm based on regional firing characteristic PCNN (RFC-PCNN) is proposed and RFI is considered as a determination to select the coefficients of source images. First, a multiscale decomposition on each source image is performed by discrete wavelet transform. Second, PCNN is employed to extract features of source images in wavelet domain. Thirdly, RFI is computed and used to combine the coefficients of source images. Finally, the fused coefficients are used to reconstruct the fused image by an inverse discrete wavelet transform. Experimental results show that the proposed algorithm outperforms the wavelet-based and wavelet-PCNN-based fusion algorithms.

关键词： image fusion Neural networks Discrete wavelet transforms Radiofrequency interference Cameras Layout Neurons Feature extraction wavelet domain image reconstruction

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An Optimal wavelet Filter for Despeckling Echocardiographic images

An Optimal Wavelet Filter for Despeckling Echocardiographic ...

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International conference on Computational Intelligence and Multimedia applications

作者： P.S. Hiremath Prema T. Akkasaligar Sharan Badiger Department of P.G. Studies & Research in Computer Science Gulbarga University Gulbarga Karnataka India Engineering College B.L.D.E.A's Dr P.G.H. Bijapur Karnataka India Departmentof Medicine Sri B. M. Patil Medical College Bijapur Karnataka India

The major difficulty concerning echocardiograph image processing is speckle noise. In this paper, we present wavelet based algorithm for denoising echocardiograph images and then determine an optimal wavelet filter that yields good quality images. The log transformed input is represented in multiscale wavelet domain. Global hard thresholding of subband coefficients is performed to achieve lossy compression of image. The inverse wavelet transformed image is free from speckle noise. The image quality is assessed in terms of objective and statistical measures, namely, peak-signal-to-noise ratio (PSNR), compression ratio, variance, mean square error (MSE). The experiments are performed using different wavelets at various levels of decomposition. The results show that bior6.8 with 2- level decomposition yields better quality despeckled images.

关键词： Filters image quality Speckle image coding PSNR image reconstruction Biomedical imaging Noise reduction Educational institutions wavelet domain

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