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Image sharpness assessment is a very important issue in image acquisition and processing. Novel approaches in no-reference image sharpness assessment methods are based on local phase coherence (LPC), rather than edge or frequency content analysis. It has been shown that the LPC based methods are closer to human observer assessments. In this paper, we propose carefully designed complex wavelets that...
Both two-dimensional Wavelet Transform and two-dimensional S Transform are common time-frequency analysis methods. The paper gives a briefly review and comparison about the two methods in the fringe pattern analysis.
Vertical stripe noise, also called waterfall artifact, is generally occurred in the line scan images. It degrades the image quality and leads to object misrecognition. This paper presents a new approach for removal of vertical stripe noise using multi-resolution wavelet decomposition. The line scan image was firstly decomposed in highest L levels using wavelet decomposition. Then the vertical component...
In recent years, image quality assessment has achieved great success. Many researchers have proposed more and more image quality assessment algorithms, which are being closer to human perception. However, some proposed algorithms could perform even better by doing some transformations on image. In this paper, a new image quality assessment based on contour let transformation is proposed. And experimental...
Bridge cable is an important part of the cable-stayed bridge, and reliable methods are necessary to ensure its safety. This paper proposes an algorithm which realizes real-time monitoring the health of bridge cable by the b-value analysis and acoustic emission technique. The algorithm can eliminate the impulse noise and the continuous noise. Discrete wavelet transform decomposes the AE signal, and...
A video summary is a sequence of still pictures that represent the content of a video in such a way that the respective target group is rapidly provided with concise information about the content, while the essential message of the original video is preserved. In this paper, we present VGRAPH, a simple yet effective video summarization approach that utilizes both color and texture features. This approach...
This paper proposes a new approach to star image denoising, recognizing and centroiding for the airborne application, especially during the daytime. To extend attitude determination of aircraft to daytime, one prerequisite is to precisely obtain the centroid of the target star. To date, there has not been an adequate analytical model and experimental method to solve this problem effectively. Generally,...
This paper presents a new method of threshold estimation for ECG signal denoising using wavelet decomposition. In this method, threshold is computed using the maximum and minimum wavelet coefficients at each level. Using this threshold and well known Hard thresholding process, the significant wavelet coefficients from each level are selected and denoised ECG signal is reconstructed with inverse wavelet...
In this paper an approach based on wavelet transform to access the on line Partial Discharge (PD) signal using MATLAB interface with Digital Storage Oscilloscope (DSO) is proposed. The noisy signal is collected and fed to computer through DSO to de-noise this using wavelet threshold technique by selecting the optimal wavelet base. From the results it shows that the de-noising performance is satisfactory,...
Automatic image registration is still a major challenge in many of the image processing applications, to name a few-remote sensing, medical imaging, industrial image analysis etc. In general, the problem of image registration can be identified as the determination of translations and a small rotation between the respective source images and generation of the resulting registered images. The most critical...
In this paper, we proposed an algorithm for estimating the density of salt & pepper noise in images with entropy inspection in wavelet domain. Based on the trait that energies of image signal and noise could be separated by wavelet transform, and on the fact that noise entropy in wavelet domain changes with approximate logarithm mode along with the noise level, we exhibit how the entropy values...
During acquisition of an image, from its source, noise becomes integral part of it, which is very difficult to remove. Various algorithms have been used in past to denoise images. Image denoising still has scope for improvement. In this paper we present a new image denoising algorithm based on combined effect of wavelet transform and median filtering. The algorithm removes most of the noisy part from...
One of the major problems encountered in recording ECG is the appearance of unwanted distortions induced by power line interference in the electrocardiogram. In addition, infections due to impulse noise leads to variations in the amplitudes which represent the abnormalities associated with the heart. This paper proposes a novel approach for addressing both the aforementioned issues in ECG signals...
In the increasingly diversified and globally integrated market environment, the accurate forecasting in the exchange markets needs to take into account the heterogeneity at both individual and cross correlation level during the modeling process. In this paper, we propose the Heterogeneous Market Hypothesis based exchange rate modeling methodology to model the micro market structure. We further propose...
Identification of dominant periodicities is a very important but difficult task in astronomical time series analysis. In the present paper, a new method of periodic identification is proposed in which empirical mode decomposition (EMD) and wavelet transform analysis (WTA) are used in combination. We firstly apply EMD method to decompose a time series into several intrinsic mode functions (IMFs), and...
Automated isotope identification has long been an important problem in homeland security and nuclear emergency response. This process is difficult for low-resolution spectra because peaks can be significantly overlapping. Also, their areas can be difficult to determine because of the fluctuating baseline due to the Compton continuum across the whole spectrum. The wavelet transform stands out among...
The measurements obtained from the acquiring PET system tend to be very noisy, since randoms and scatter contamination events as well as detector efficiency are strong sources of noise. In particular, for the small animal reconstructed images, this problem becomes severe corrupting areas of interest between organs, making the identification process even more difficult. For that reason, a regularization...
Most of the current pitch detection algorithms can not work well under the high noise environment. For this reason, a pitch detection algorithm for noisy speech signals based on wavelet transform and autocorrelation function is proposed. First, the noisy speech signals are decomposed by three-layer wavelet transform in order to get rid of the high frequency noise and obtain the approximate signals...
In most situations, acquired digital images always are corrupted by the wrong camera focus, serious illumination even missing data. This algorithm is presented for fusion of corrupted multi-sensor images by noise. Compared to the susceptible properties of PCA by large errors, the proposed method includes adaptive fusion arithmetic based on matrix completion and self-adaptive regional variance estimation...
A fresh image denoising algorithm using neighboring coefficients of nonsubsampled contourlet transform (NSCT) is presented. NSCT can obtain better results compared to traditional wavelets and contourlet transform due to its outstanding properties. But denoising by NSCT using classical threshold doesn't take account of coefficients correlation. Noise suppressing method presented calculates the hard...
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