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检索条件"任意字段=Wavelet Applications in Signal and Image Processing VIII"

共 3982 条记录，以下是721-730 订阅

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Noise Reducing Using Hybrid Technique In Magnetic Resonances image

Noise Reducing Using Hybrid Technique In Magnetic Resonances...

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作者： Samah Gaysar Musa Sudan University of Science and Technology

学位级别：硕士

Several new techniques are developed within the previous couple of years that convalesce results on special filters by take away the noise additional with success whereas protective the sides within the information. image de-noising plays an important role in satellite communication and signal processing applications. In this research, I suggest an median filter, NLmeansfilter, Total Variation (TV), Hybrid Median Filtering (hmedian), Speckle Reducing Anisotropic Diffusion Filtering (srad) and Bilateral Filter and adaptive discreet wavelet technique for image de-noising. The noisy image is passed through One level discrete wavelet transform is applied, which is passed through post-processing hybrid median filter to remove noise in high-high coefficients. Finally, The Inverse discrete wavelet transform is applied to reconstruct the image.. The image quality is measured to reconstruct image. I have a tendency to take PSNR, SNR, RMES and MSE as a potency issue to envision the effectiveness of planned de-noising formula.

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Content Based image Retrieval by Combining Feature Vector

Content Based Image Retrieval by Combining Feature Vector

引用

IEEE International Conference on Wireless Communications, signal processing and Networking (WiSPNET)

作者： Ruikar, S. D. Kabade, Rohit S. Walchand Coll Engn Dept Elect Engn Sangli India PVPIT Budhgaon Elect & Comm Engn Dept Sangli India

ISBN: (纸本)9781467393379

This paper describes the searching problem of images stored in big databases i.e. content based image retrieval (CBIR) system. It represents the behaviour and proposes solution for it. In general vast deployment in various applications therefore the capacity of image database increases because it's needed efficient CBIR method. This paper uses the primary image features like colour, shape and texture. This primary features take out using various algorithms those are useful to obtain similarity check into images. It describes the result using MATLAB software application, with a large image database. It utilizes feature of colour, texture and shape of the database images for comparison purpose and further for obtaining of image and it including relevance.

关键词： Color shape texture wavelet etc

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Objective Smoothness Metric for Just Noticeable Blur Estimation 9

Objective Smoothness Metric for Just Noticeable Blur Estimat...

引用

9th International Congress on image and signal processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Lee, Mong-Shu Chiu, Kuan-Chih Natl Taiwan Ocean Univ Dept Comp Sci & Engn Keelung Taiwan

ISBN: (纸本)9781509037100

An objective blur measure is crucial for a variety of image processing applications, Traditional researches concentrate on a model estimating the amount of spatial high frequency. However, human vision detects blurriness might be influenced by the texture of image contents. To address the important issue, this paper presents a new objective metric designed as both measuring the inherent smooth texture and predicting the difference induced by blur distortion. The approach is based on the wavelet characterization of Besov function spaces and just noticeable difference of human vision. Then, the just noticeable blur is estimated from the derived psychometric function using the proposed metric and subjective scores. Experimental comparisons with state-of-the-arts quality metrics for public data bases show that the proposed metric achieved high correlation with the general objective quality or subjective metrics.

关键词： just noticeable difference psychometric function Besov space image quality assessment blur distortion

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Surface reconstruction with wavelet transformation 20

Surface reconstruction with Wavelet transformation

引用

20th Jubilee IEEE International Conference on Intelligent Engineering Systems (INES)

作者： Balla, Petra Kocsis, Peter Eigner, Gyorgy Antal, Akos BUTE Dept Mechatron Opt & Mech Engn Informat Budapest Hungary Obuda Univ Res & Innovat Ctr Physiol Controls Grp Budapest Hungary

ISBN: (纸本)9781509012169

The development in computing power highlights some forgotten algorithms, which were neglected because of their complexity and slowness on early computers. One example is the wavelet-Transformation Profilometry (WTP) of which successful application is demonstrated in the paper. WTP is a high level signal processing method using orthogonal algorithms for huge datasets. The high performance in quality and running speed makes the described method suitable for medical image processing applications.

关键词： processing

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Automated Detection of Current Fetal Head in Ultrasound Sequences 2

Automated Detection of Current Fetal Head in Ultrasound Sequ...

引用

2nd International Conference on image processing, applications and Systems (IPAS)

作者： Sahli, Hanene Ben Slama, Amine Zaafouri, Ahmed Sayadi, Mounir Rachdi, Rathwen Univ Tunis ENSIT Lab SIME Tunis Tunisia Mil Hosp Dept Matern Tunis Tunisia

ISBN: (纸本)9781509016457

Accurate diagnostic and prognostic of fetus detects is an important challenge based on fetal head formation to supply much critical information that requires more attention in evaluating the abnormal heads. One of the fundamental problems currently faced, is how to limit the low signal to noise ratio with respect to the complexity of small fetal head ultrasound images dimension. This paper deals with a fully automatic detection system of subsequent fetal head composition from ultrasound images. In the preprocessing task, two filters have been used for speckle noise reducing. Using the Hough transform technique, fetal head structure detection is achieved, giving 97% as segmentation accuracy. Experimental results are analyzed using five ultrasound sequences that illustrate the effectiveness and the accuracy of the proposed method for a factual diagnostic of fetal heads.

关键词： fetal head ultrasound images Hough transform anisotropic diffusion discrete wavelet transform

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Custom Instruction for NIOS II processor FFT implementation for image processing

Custom Instruction for NIOS II processor FFT implementation ...

引用

Conference on Sensing and Analysis Technologies for Biomedical and Cognitive applications

作者： Sundararajan, Sindhuja Meyer-Baese, Uwe Botella, Guillermo FAMU FSU ECE Dept 2525 Pottsdamer St Tallahassee FL 32310 USA Univ Complutense Madrid Dept Comp Architecture E-28040 Madrid Spain

ISBN: (纸本)9781510601123

image processing can be considered as signal processing in two dimensions (2D). Filtering is one of the basic image processing operation. Filtering in frequency domain is computationally faster when compared to the corresponding spatial domain operation as the complex convolution process is modified as multiplication in frequency domain. The popular 2D transforms used in image processing are Fast Fourier Transform (FFT), Discrete Cosine Transform (DCT) and Discrete wavelet Transform (DWT). The common values for resolution of an image are 640x480, 800x600, 1024x768 and 1280x1024. As it can be seen, the image formats are generally not a power of 2. So power of 2 FFT lengths are not required and these cannot be built using shorter Discrete Fourier Transform (DFT) blocks. Split radix based FFT algorithms like Good-Thomas FFT algorithm simplifies the implementation logic required for such applications and hence can be implemented in low area and power consumption and also meet the timing constraints thereby operating at high frequency. The Good-Thomas FFT algorithm which is a Prime Factor FFT algorithm (PFA) provides the means of computing DFT with least number of multiplication and addition operations. We will be providing an Altera FPGA based NIOS II custom instruction implementation of Good-Thomas FFT algorithm to improve the system performance and also provide the comparison when the same algorithm is completely implemented in software.

关键词： DFT FFT DCT DWT PFA FPGA NIOS image processing

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Dyadic Lifting wavelet Based signal Detection 3

Dyadic Lifting Wavelet Based Signal Detection

引用

3rd International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2016

作者： Kuzume, Koichi Tabusa, Tomonori Department of Information Science Engineering Institute of Technology Yuge College Ehime-ken Japan

ISBN: (纸本)9781467391870

Local regularities of a signal contain important information such as edges in an image and QRS complexes in an Electrocardiogram (ECG). In order to detect such local regularities in the signal, wavelet transform has been focused on as a powerful tool for signal processing applications. wavelet maxima at the time in which the signal abruptly changes are usually large in amplitude. However, with only the magnitude of the wavelet maxima the features of the signal cannot be known in detail. Mallat et al. proposed the Lipchitz regularity for observing signal cross scales in multiresolution signal analysis, but its computational cost was relatively expensive. This paper presents a novel method for signal detection using lifting dyadic wavelet transform, which has the time-invariant property. The lifting wavelet parameters contained in Swelden's formula were tuned, adapting them to the signals to be detected. The method for tuning these parameters was to learn the features of the target signals in the multiresolution analysis. To evaluate our methods we applied them to detect the QRS complexes contained in an ECG. The results showed that our methods were useful to detect target signals accurately. © 2016 IEEE.

关键词： signal detection

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DESIGN OF EFFECTIVE LOW POWER image COMPRESSION ALGORITHM

DESIGN OF EFFECTIVE LOW POWER IMAGE COMPRESSION ALGORITHM

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IEEE International Conference on Wireless Communications, signal processing and Networking (WiSPNET)

作者： Epshi, G. Saravanan, V. Venkatalakshmi, B. Velammal Engn Coll Madras 600066 Tamil Nadu India

ISBN: (纸本)9781467393379

For satellite communication, large amount of data storage and transmission are involved as the satellites send data all the time, all day. Storing all these data and analyzing them for various purposes is possible using small low cost memory devices only with the help of image compression. image compression is the process of removing the redundant information from the image and it can be stored to reduce the storage size, transmission bandwidth and time. image compression aims at removing duplication from the source image and is essential for applications such as transmission and storage in an efficient form. The objective of the work is to develop an efficient low power image compression algorithm which compress it with higher compression ratio in such a way that the output compressed image becomes compatible for satellite communication. The proposed system should own a light weight algorithm which has the characteristics of minimum power consumption, less compression time and should meet a higher compression ratio. To do image compression, quad tree fractal image compression and an adaptive fractal wavelet image compression algorithm are selected and their performance in terms of mean square error, ratio of compression and peak signal to noise ratio are evaluated.

关键词： Fractal range block image compression quad tree

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Local Gabor wavelet-Based Feature Extraction and Evaluation 3rd

Local Gabor Wavelet-Based Feature Extraction and Evaluation

引用

3rd International Conference on Advanced Computing, Networking, and Informatics (ICACNI)

作者： Malathi, T. Bhuyan, M. K. Indian Inst Technol Dept Elect & Elect Engn Gauhati 781039 India

ISBN: (纸本)9788132225386;9788132225379

Feature extraction is an essential step in many image processing and computer vision applications. It is quite desirable that the extracted features can effectively represent an image. Furthermore, the dominant information visually perceived by human beings should be efficiently represented by the extracted features. Over the last few decades, different algorithms are proposed to address the major issues of image representations by the efficient features. Gabor wavelet is one of the most widely used filters for image feature extraction. Existing Gabor wavelet-based feature extraction methodologies unnecessarily use both the real and the imaginary coefficients, which are subsequently processed by dimensionality reduction techniques such as PCA, LDA etc. This procedure ultimately affects the overall performance of the algorithm in terms of memory requirement and the computational complexity. To address this particular issue, we proposed a local image feature extraction method by using a Gabor wavelet. In our method, an image is divided into overlapping image blocks, and subsequently each of the image blocks are separately filtered out by Gabor wavelet. Finally, the extracted coefficients are concatenated to get the proposed local feature vector. The efficacy and effectiveness of the proposed feature extraction method is evaluated using the estimation of mean square error (MSE), peak signal-to-noise ratio (PSNR), and the correlation coefficient (CC) by reconstructing the original image using the extracted features, and compared it with the original input image. All these performance evaluation measures clearly show that real coefficients of the Gabor filter alone can effectively represent an image as compared to the methods which utilize either the imaginary coefficients or the both. The major novelty of our method lies on our claim-capability of the real coefficients of a Gabor filter for image representation.

关键词： image feature extraction Gabor filter image reconstruction

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Human Age Classification using Facial Skin Analysis and Multi-class Support Vector Machine

Human Age Classification using Facial Skin Analysis and Mult...

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International Conference on signal and Information processing (IConSIP)

作者： Jagtap, Jayant Kokare, Manesh SGGS Inst Engn & Technol Dept Elect & Telecommun Engn Vishnupuri 431606 Nanded India

ISBN: (纸本)9781509015221

Human age classification via face images becoming an interesting research area because of potential applications in the field of computer vision such as Age Specific Human Computer Interaction (ASHCI), biometrics, security and surveillance, etc. In this paper, a novel method for human age classification using facial skin analysis for aging feature extraction and Multi-class Support Vector Machine (M-SVM) for age classification is proposed to classify the face images into four age groups. Facial skin analysis consists of skin texture analysis and wrinkle analysis. Gabor wavelet is used to analyze the facial skin textural changes with age progression. Wrinkle analysis detects the wrinkle density changes at particular regions on face image with age progression. The performance evaluation of proposed age classification system is carried out by using face images from PAL face database. In this paper, the performance of M-SVM classifier is compared with the performance of Artificial Neural Network ( ANN) classifier for the task of human age classification using Gabor wavelet and wrinkle analysis. The result analysis concludes that the best age classification accuracy of 93.61% is achieved by using proposed age classification system and M-SVM is an efficient classifier than the ANN classifier for the task of human age classification in combination with Gabor wavelet and wrinkle analysis.

关键词： Facial skin analysis Gabor wavelet Wrinkle analysis Multi-class Support Vector Machine (M-SVM) Artificial Neural Network (ANN)

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