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) o...
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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 signalprocessing method using orthogonal algorithms for huge datasets. The high performance in quality and running speed makes the described method suitable for medical imageprocessingapplications.
Information fusion consists in combining information in order to maximize the relevant information and reduce the redundancy. It is widely used in many fields, especially in imageprocessing, for analyzing situations....
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ISBN:
(纸本)9781509016457
Information fusion consists in combining information in order to maximize the relevant information and reduce the redundancy. It is widely used in many fields, especially in imageprocessing, for analyzing situations. Since the first use of the information fusion concept, many approaches have been introduced to define a processing model to merge information. Three basic approaches are used in information fusion: the JDL Model which is the first one used, the Intelligence Cycle Model and the DFD (Data - Features - Decision) Model. According to the field of application and the type of the information manipulated, the processing model is different. In imageprocessing, various techniques and methods are used to perform image fusion. Many techniques are most used in research studies: PCA (Principal Component Analyses), wavelet transform,. In this paper we present a general overview of the basic models and techniques used in image fusion.
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 va...
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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.
We propose a non-iterative image deconvolution algorithm for data corrupted by Poisson noise. Many applications involve such a problem, ranging from astronomical to biological imaging. We parametrize the deconvolution...
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ISBN:
(纸本)9781467399616
We propose a non-iterative image deconvolution algorithm for data corrupted by Poisson noise. Many applications involve such a problem, ranging from astronomical to biological imaging. We parametrize the deconvolution process as a linear combination of elementary functions, termed as linear expansion of thresholds (LET). This parametrization is then optimized by minimizing a robust estimate of the mean squared error, the "Poisson unbiased risk estimate (PURE)". Each elementary function consists of a Wiener filtering followed by a pointwise thresholding of undecimated Haar wavelet coefficients. In contrast to existing approaches, the proposed algorithm merely amounts to solving a linear system of equations which has a fast and exact solution. Simulation experiments over various noise levels indicate that the proposed method outperforms current state-of-the-art techniques, in terms of both restoration quality and computational time.
Accurate detection and localization of vehicles in aerial images has a wide range of applications including urban planning, military reconnaissance, visual surveillance, and real-time traffic management. Automated det...
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ISBN:
(纸本)9781467399616
Accurate detection and localization of vehicles in aerial images has a wide range of applications including urban planning, military reconnaissance, visual surveillance, and real-time traffic management. Automated detection of vehicles in aerial imagery is a challenging task, due to the density of vehicles on the road. the complexity of the surrounding environment in urban areas, and low spatial resolution of the image sensor array. We propose an automated method for detecting vehicles of varying sizes in low-resolution aerial imagery. First, we develop a new vehicle enhancement filter involving multiscale Hessian analysis. After thresholding, we refine the candidate vehicle detections based on analysis of bilateral symmetry. We show that our proposed method provides improved detection accuracy compared with existing vehicle detection algorithms for various low-resolution aerial images.
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 b...
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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 usi...
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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 waveletimage compression algorithm are selected and their performance in terms of mean square error, ratio of compression and peak signal to noise ratio are evaluated.
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, sec...
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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.
Wireless Sensor Networking is a sensor information gathering technology that has a wide range of applications in numerous fields. However due to the fact that sensor nodes have limited battery and are deployed in remo...
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ISBN:
(纸本)9781467393379
Wireless Sensor Networking is a sensor information gathering technology that has a wide range of applications in numerous fields. However due to the fact that sensor nodes have limited battery and are deployed in remote and harsh environments, energy efficient and real time transmission of the information are still open challenges. Since in a wireless sensor network data transmission is the most power consuming task, so far most useful techniques for the purpose of energy efficient and real time transmissions are based on data compression, the majority of them are based on wavelet transform. This paper give performance analysis of different wavelets for energy efficient and real time image data transmission in application like environment monitoring using wireless visual sensor networks. The performance evaluation shows that Haar wavelet is better in terms of energy efficiency and transmission time.
Speech signalprocessing is widely used to reduce noise impact in acquired data. During the last decades, wavelet-based filtering techniques are often applied in communication systems due to their advantages in signal...
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ISBN:
(纸本)9781628419412
Speech signalprocessing is widely used to reduce noise impact in acquired data. During the last decades, wavelet-based filtering techniques are often applied in communication systems due to their advantages in signal denoising as compared with the Fourier-based methods. In this study we consider applications of a 1-D double density complex wavelet transform (1D-DDCWT) and compare the results with the standard 1-D discrete wavelet-transform (1D-DWT). The performances of the considered techniques are compared using the mean opinion score (MOS) being the primary metric for the quality of the processed signals. A two-dimensional extension of this approach can be used for effective image denoising.
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