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Threshold selection is the critical issue in image denoising. This paper deal with a new multiscale directional representation called the shearlet transform that has shown to represent specific classes of images with distributed discontinuities optimally. Techniques based on this transform for denoising using an efficient adaptive shrinkage threshold are presented. The shearlet transform not only...
This paper presents a method based on S-transform and artificial neural network for detection and classification of power quality disturbances. The input features of the neural network are extracted using S-transform. The features obtained from the S-transform are distinct, understandable and immune to noise. These features after normalization are given to a feed forward neural network trained by...
In this paper, we propose a new method to extract object contour in a given gray-level image, whose foreground and background are statistically homogeneous and different. Firstly, the image for contour extraction is decomposed by discrete wavelet transform, and the high-pass and low-pass components are used to form intensity and texture energy respectively. Secondly, a minimal partition function,...
The classic wavelet transform has been applied in registration and fusion of medical images for decades. An extension namely, contourlet transform recently indicated its advantages in image fusion with better efficiency in multi-resolution and multi-direction representation and calculation. However, then even higher computational complexity it requires turns out to be a disastrous concern in embedded...
Semi-fragile watermark has attracted attention due to its important role in content authentication for multimedia. In order to distinguish malicious tampering from incidental attacks, semi-fragile watermark must be robust against content-protection image processing. Due to the widely use of JPEG compression, it is always an important subject of semi-fragile watermarking research to improve the performance...
In this paper, we present a novel algorithm for robust audio watermarking in image using wavelet transform based on an image entropy. The motivation of choosing image as a cover is driven by the fact that human visual system is less sensitive than human auditory system thus an image provides better masking effect. The algorithm is based on decomposition of images using Daubechies wavelet basis. The...
A pixel-level fusion approach is proposed to refine the resolution of urban multi-spectral images using the corresponding high-resolution panchromatic images. After the two images are decomposed by wavelet transform, three texture features are extracted from high-frequency detailed sub-images. Then a fuzzy fusion rule is used to merge wavelet coefficients from the two images according to the extracted...
With the growing demand for improving reliability and performance of turbo-generator set as an important power supply in modern electric industry, the vibration signal processing and fault diagnosis techniques have been developed for dynamic feature extraction and pattern recognition. A new approach using wavelet transform and fuzzy network modeling is presented for vibration fault diagnosis of turbo-generator...
The analysis of the electrocardiogram (ECG) is widely used for diagnosing many cardiac diseases. Since most of the clinically useful information in the ECG is found in characteristic wave peaks and boundaries, a significant amount of research effort has been devoted to the development of accurate and robust algorithms for automatic detection of the major ECG characteristic waves (i.e., the QRS complex,...
The diffusion weighted imaging (DWI) technique can be utilized to investigate a variety of diseases. We propose an automated system which assists the diagnosis of metabolic brain diseases clinically. In this study, DWI images are preprocessed and exponential apparent diffusion coefficient (eADC) images are produced. The eADC images are later brain extracted and normalized to a standard brain atlas...
With the use of advanced computer graphics rendering software, very successful photorealistic images can be generated. Therefore, it may be hard to discriminate the photographic images from the photorealistic ones. In this work, we propose to use the statistics obtained from the ridgelet transform to distinguish the photographic and photorealistic images. Experimental results show that the features...
Forest fire detection includes satellite monitoring, manual monitoring, aerial survey and so on. Compared with these expensive ways, a more practical fireproofing surveillance system needs to be built. An image capture system can be set up in the tower to sent fire image back to the command centre, using the short wave radios equipped for manual monitoring in the towers. Considering the finitude of...
Owing to the stochastic nature of discrete processes such as photon counts in imaging, a variety of real-world data are well modeled as Poisson random variables whose means are in turn proportional to an underlying vector-valued signal of interest. Certain wavelet and filterbank transform coefficients corresponding to measurements of this type are distributed as sums and differences of Poisson counts,...
Detection, localization and quantification of voltage and current disturbances are important tasks in monitoring and protection of distribution systems. The concept of discrete wavelet transform for feature extraction of power quality disturbance signals has been incorporated as a powerful tool for detecting and classifying power quality problems. This paper presents the ability of multiresolution...
A common goal of biotechnological research and of commercial production is the definition of optimum conditions for achieving predetermined objectives. This goal is usually translated into the problem of finding the optimum control strategy that will produce the desired end-product. Today's fermentation controllers rely mostly on environmental state variables which only provide information on the...
In this paper we present a novel appearance based approach to the problem of face pose classification. This method suggests the subject-independent pose classification of face images using bilateral filtering and wavelet transform as preprocessing and isometric projection based subspace learning for the extracting of discriminant feature vectors. Our proposed method is evaluated on a large image set...
A video activity analysis is presented based on 3D wavelet transform. Marginal and joint statistics as well as mutual information estimates are extracted. Marginal histograms are approximated by generalized Gaussian density (GGD) functions. The mutual information between coefficients -as a quantitative estimate of joint statistics- decreases when the activity in the video increases. The relationship...
This paper is based on the multi-scale analysis of the wavelet transform. By detecting the part modulus maximum of the planar wavelet transformation coefficient, it can acquire the image edge feature of the rubber gasket and demonstrate the feasibility and advantages of Gaussian function, especially the smoothing function. This method successfully retains the edge information of rubber gasket and...
In this paper, a watermarking algorithm for ROI (Regions of Interesting) authentication and tamper detection is proposed. The watermarking is embedded in the DWT (Discrete Wavelet Transform) coefficients of the ROB (Regions of Background). The algorithm uses a hashing to detect whether the ROI of image is tampered, and then uses the watermarking to reconstruct the data of ROI. The experiment results...
Wavelet transform has demonstrated its exception power on digital imaging processing, moreover in recent decades wavelet time-frequency distribution has been successfully applied into the biomedical images decomposition and reconstruction process including analysis and integration of electromyography (EMG). Whereas in medical practice one of the major drawbacks in clinical EMG diagnosis lies in the...
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