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image and video processing using discrete fractional transforms

signal image AND VIDEO processing 2014年第8期8卷 1543-1553页

作者： Jindal, Neeru Singh, Kulbir Thapar Univ Dept ECE Patiala 147004 Punjab India

The mathematical transforms such as Fourier transform, wavelet transform and fractional Fourier transform have long been influential mathematical tools in information processing. These transforms process signal from time to frequency domain or in joint time-frequency domain. In this paper, with the aim to review a concise and self-reliant course, the discrete fractional transforms have been comprehensively and systematically treated from the signal processing point of view. Beginning from the definitions of fractional transforms, discrete fractional Fourier transforms, discrete fractional Cosine transforms and discrete fractional Hartley transforms, the paper discusses their applications in image and video compression and encryption. The significant features of discrete fractional transforms benefit from their extra degree of freedom that is provided by fractional orders. Comparison of performance states that discrete fractional Fourier transform is superior in compression, while discrete fractional cosine transform is better in encryption of image and video. Mean square error and peak signal-to-noise ratio with optimum fractional order are considered quality check parameters in image and video.

关键词： Discrete fractional Fourier transforms Discrete fractional Cosine transforms Discrete fractional Hartley transforms image Video

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Atomic decompositions of fuzzy normed linear spaces for wavelet applications

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Informatica (Netherlands) 2014年第4期25卷 643-662页

作者： Nadaban, Sorin Dzitac, Ioan Department of Mathematics and Computer Science Aurel Vlaicu University of Arad Elena Dragoi 2 AradRO-310330 Romania Department of Social Sciences Agora University of Oradea Piata Tineretului 8 OradeaRO-485526 Romania

wavelet analysis is a powerful tool with modern applications as diverse as: image processing, signal processing, data compression, data mining, speech recognition, computer graphics, etc. The aim of this paper is to introduce the concept of atomic decomposition of fuzzy normed linear spaces, which play a key role in the development of fuzzy wavelet theory. Atomic decompositions appeared in applications to signal processing and sampling theory among other areas. First we give a general definition of fuzzy normed linear spaces and we obtain decomposition theorems for fuzzy norms into a family of semi-norms, within more general settings. The results are both for Bag-Samanta fuzzy norms and for Katsaras fuzzy norms. As a consequence, we obtain locally convex topologies induced by this types of fuzzy norms. The results established in this paper, constitute a foundation for the development of fuzzy operator theory and fuzzy wavelet theory within this more general frame. © 2014 Vilnius University.

关键词： Data handling

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Using image processing on MRI Scans

Using Image Processing on MRI Scans

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IEEE International Conference on signal processing, Informatics, Communication and Energy Systems (SPICES)

作者： Chetan Patil M G Mathura S Madhumitha S Sumam David Merwyn Fernandes Anand Venugopal B. Unnikrishnan Dept. of E&C NITK Surathkal Mangalore 575025 India Dept. of Radiology Kasturba Medical College Mangalore 575001 India Dept. of Community Medicine Kasturba Medical College Mangalore 575001 India

Alzheimer's disease (AD) is an irreversible and progressive brain disease that gradually destroys memory and thinking skills to an extent that it starts affecting the daily life. It has become the most common cause of dementia among older people. The work presented in this paper evaluates the utility of image processing on the Magnetic Resonance Imaging (MRI) scans to estimate the possibility of an early detection of AD. The total brain atrophy and specifically the hippocampal atrophy are considered strong diagnostic tests for AD. T1 weighted MRIs have been used for the purpose of image processing to evaluate atrophy. The paper demonstrates the applications of several image processing techniques such as K-means clustering, wavelet transform, watershed algorithm and also a customized algorithm tailored for the specific case. It has been implemented on the open source platforms, OpenCV and Qt, which facilitates the implementation and utility of the developed product in the hospitals without requiring any proprietary software. The results obtained from the project could aid the analysis to detect AD along with correlation with the psychiatric results and could thus assist the doctors in detecting AD at an early stage. This could progressively help in understanding and treating AD.

关键词： Atrophy Magnetic resonance imaging Alzheimer's disease Hippocampus Medical diagnostic imaging

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Pan-sharpening based on weighted red black wavelets

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IET image processing 2014年第8期8卷 477-488页

作者： Liu, Qingjie Wang, Yunhong Zhang, Zhaoxiang Liu, Lining Beihang Univ Sch Comp Sci & Engn State Key Lab Virtual Real Technol & Syst Beijing 100191 Peoples R China

Pan-sharpening is a technique which provides an efficient and economical solution to generate multi-spectral (MS) images with high-spatial resolution by fusing spectral information in MS images and spatial information in panchromatic (PAN) image. In this study, the authors propose a new pan-sharpening method based on weighted red-black (WRB) wavelets and adaptive principal component analysis (PCA), where the usage of WRB wavelet decomposition is to extract the spatial details in PAN image and the adaptive PCA is used to select the adequate principal component for injecting spatial details. WRB wavelets are data-dependent second generation wavelets. Multi-resolution analysis (MRA) based on WRB wavelet transform shows a better de-correlation of the data compared with common linear translation-invariant MRA, which makes it suitable for applications requiring manipulating image details. A local processing strategy is introduced to reduce the artefact effects and spectral distortions in the pan-sharpened images. The proposed method is evaluated on the datasets acquired by QuickBird, IKONOS and Landsat-7 ETM + satellites and compared with existing methods. Experimental results demonstrate that the authors method can provide promising fused MS images with high-spatial resolution.

关键词： image resolution weighted red black wavelets-based pan-sharpening adaptive PCA WRB wavelet decomposition WRB wavelet transform spectral analysis image manipulation panchromatic image IKONOS Computer vision and image processing techniques PAN image image fusion high-spatial image resolution Optical, image and video signal processing Integral transforms linear translation-invariant MRA spectral information fusion MRA principal component analysis economical solution wavelet transforms MS image generation adaptive principal component analysis Landsat-7 ETM QuickBird multispectral image generation spectral distortions data-dependent second generation wavelets Other topics in statistics

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小波降噪在Matlab与ADSP 21160中的实现

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计算机应用 2015年第A1期35卷 243-246,272页

作者：杨璐宇昆明船舶设备研究试验中心昆明650051

小波算法具有对信号时间或空间频率的局部化分析能力,能自适应非稳定信号分析的需求,已经逐渐成为DSP的主流。通常小波算法在信号降噪处理中的研究都是在软件上实现的,且处于非实时状态,为了满足信号降噪的实时处理需求,需使用硬件来实... 详细信息

小波算法具有对信号时间或空间频率的局部化分析能力,能自适应非稳定信号分析的需求,已经逐渐成为DSP的主流。通常小波算法在信号降噪处理中的研究都是在软件上实现的,且处于非实时状态,为了满足信号降噪的实时处理需求,需使用硬件来实现小波算法。分析小波算法在Matlab中提供的具体软件实现流程,根据该流程将小波降噪算法移植到ADI公司SHARC系列产品之一的ADSP 21160芯片上,并以汇编语言的形式实现,以达到快速、实时、高效降低信号噪声的目的,为小波降噪提供实时处理平台。分别在ADSP 21160仿真器与Matlab上实验,比较结果表明,在ADSP 21160芯片上使用小波变换对信号降噪处理可以很好地满足信号降噪实时处理的要求。

关键词：小波算法降噪处理信号处理 Matlab ADSP 21160

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Adaptive digital watermarking using RDWT and SVD

Adaptive digital watermarking using RDWT and SVD

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IEEE International Workshop on Haptic, Audio and Visual Environments and Their applications

作者： Lei Chen Jiying Zhao School of Electrical Engineering and Computer Science University of Ottawa Ottawa ON Canada

This paper proposes a new scheme for secure digital watermarking and copyright protection of videos. The approach presented here is based on redundant discrete wavelet transform (RDWT) and singular value decomposition (SVD). The video frames and the watermark are decomposed by RDWT, and the watermark is embedded into the subbands of the I-frames. The singular values of the I-frames are modified with the singular values of the visual watermark. Meanwhile, the watermark embedding strength is adjusted adaptively using the noise visibility function (NVF) with local properties. The approach is efficient and appropriate for real-time applications. The experimental results demonstrate that the proposed approach has good performance in preserving high quality of the video, and the watermark can be extracted accurately after various attacks.

关键词： Watermarking Videos Discrete wavelet transforms Robustness signal processing algorithms image color analysis

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DWT Subbands Fusion Using Ant Colony Optimization For Edge Detection

DWT Subbands Fusion Using Ant Colony Optimization For Edge D...

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22nd IEEE signal processing and Communications applications Conference (SIU)

作者： Muhammad, Aminu Bala, Ibrahim Salman, Mohammad Shukri Eleyan, Alaa Mevlana Rumi Univ Elect & Elect Engn Dept Selcuklu Konya Turkey

ISBN: (纸本)9781479948741

In this paper, a new approach for image edge detection using wavelet based ant colony optimization (ACO) is proposed. The proposed approach applies discrete wavelet transform (DWT) on the image. ACO is applied to the generated four subbands (Approximation, horizontal, vertical, and diagonal) separately for edge detection. After obtaining edges from the 4 subbands, inverse DWT is applied to fuse the results into one image with same size as the original one. The proposed approach outperforms the conventional ACO approach.

关键词： ant colony optimization discrete wavelet transform edge detection

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Block Based Robust Blind image Watermarking Using Discrete wavelet Transform

Block Based Robust Blind Image Watermarking Using Discrete W...

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IEEE 10th International Colloquium on signal processing and its applications (CSPA)

作者： Kakkirala, Krishna Rao Chalamala, Srinivasa Rao HiTec City TATA Consultancy Serv TCS Innovat Labs Hyderabad Andhra Pradesh India

ISBN: (纸本)9781479930913

Digital watermarking is a process to provide authenticity by hiding a data into an image or audio or document. Hiding of data in an image can be done in frequency domain. Since frequency domain based techniques are more robust against signal processing and geometric attacks than time domain based techniques and watermark can also be extracted with(non blind) and without(blind) original cover image. In this paper we proposed a blind image watermarking technique which embeds watermark into image in frequency domain using discrete wavelet transform, singular value decomposition and torus automorphism techniques. This technique extracts watermark without cover image and also proved that this method is robust against different signal and non signal processing attacks.

关键词： discrete wavelet transform dwt singular value decomposition svd torus automorphism watermark psnr

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applications of multi-wavelet transform in remote-sensing image fusion

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International Journal of Earth Sciences and Engineering 2014年第6期7卷 2461-2467页

作者： Chen, Dangui Chen, Hui Tang, Jia Gao, Haibo Hunan International Economics University ChangshaHunan China

With the development of sensor technology, an increasingly number of remote-sensing image data with different spatial resolutions and spectral resolutions will be applied in the engineering and remote-sensing image fusion has become an important research area in the current research fields of remote-sensing application. As a new mathematical theory, multi-wavelet theory has been widely applied in such fields as signal analysis and image processing quickly, especially after Mallat proposed the fast algorithm of wavelet decomposition and reconstruction. This paper mainly fuses the panchromatic remote-sensing image (SPOT) of high spatial resolution and the multispectral remote-sensing image (TM) of low spatial resolution by using multi-wavelet theory and IHS transform so as to improve the preservation of multi-spectral information and the performance ability of spatial details in the fused image. The analysis of the experiment result verifies the feasibility and effectiveness of the method of this paper to achieve relatively ideal effect. © 2014 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved.

关键词： image fusion

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Comparative Analysis of wavelet TRANSFORM ALGORITHMS for image COMPRESSION 3

Comparative Analysis of WAVELET TRANSFORM ALGORITHMS for IMA...

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3rd International Conference on Communications and signal processing (ICCSP)

作者： Kourav, Arvind Sharma, Ashutosh Dr KN Modi Univ Newai Rajasthan India Globus Engn Coll Elect & Commun Engn Dept Bhopal India

ISBN: (纸本)9781479933587

The basic objective of this paper is to analyze the concept of wavelet based algorithms for image compression using different parameter. All algorithms are based on still images, The algorithm involved in the comparative analysis is wavelet Difference Reduction (WDR), Spatial orientation tree wavelet (STW), Embedded zero tree wavelet (EZW) and modified Set Partitioning in hierarchical trees (SPIHT). These algorithms are more effective and deliver a better feature in the image. In compression, wavelets transform have shown a good elasticity to a large amount of data, while being of realistic complexity. These techniques are used in many image processing applications. The techniques are compared by using the performance parameters peak signal to noise ratio (PSNR) & mean square error (MSE).

关键词： wavelet transforms WDR STW EZW Modified SPIHT and image Compression

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