An increasingly popular approach to the acquisition of intraoperative data is the novel Time-of-Flight (ToF) camera technique, which provides surface information with high update rates. This information can be used for intra-operative registration with pre-operative data through surface matching techniques. However, ToF data is subject to different systematic errors and noise, which must be eli...

This is a short summary of a talk given at the Frontier Science in EEG Symposium, Continuous Waveform Analysis, held on 9 October 1993 in New Orleans. We describe some new libraries of waveforms well-adapted to various numerical analysis and signal processing tasks. The main point is that by expanding a signal in a library of waveforms which are well-localized in both time and frequency, one ca...

Accuracy of microarray gene expression based cancer classification depends on microarray image processing techniques. Image de-noising is one of the crucial step of the microarray image processing. Better the quality of microarray image, more accurate will be the result of cancer classification. In this paper, we have implemented Median filter and wavelet transform based filters with various th...

Tracking problem in spherical coordinates with range rate (Doppler) measurements, which would have errors correlated to the range measurement errors, is investigated in this paper. The converted Doppler measurements, constructed by the product of the Doppler measurements and range measurements, are used to replace the original Doppler measurements. A de-noising method based on an unbiased Kalma...

This paper shows a relationship between two diierent approximation techniques: the Support Vector Machines (SVM), proposed by V. Vapnik (1995), and a sparse approximation scheme that resembles the Basis Pursuit De-Noising algorithm (Chen, 1995; Chen, Donoho and Saunders, 1995). SVM is a technique which can be derived from the Structural Risk Minimization Principle (Vapnik, 1982) and can be used...

Electrocardiogram (ECG) signal plays an important role in the diagnosis of cardiovascular disease. However, ECG signal is very faint and always affected by a variety of noise in the process of collecting. How to eliminate the noise effectively is an important issue and has been widely studied for many years. In this paper, we propose a new ECG de-noising method based on translation invariant (T...

Since time immemorial, noise has been a constant source of disturbance to the various entities known to mankind. Noise models of different kinds have been developed to study noise in more detailed fashion over the years. Image processing, particularly, has extensively implemented several algorithms to reduce noise in photographs and pictorial documents to alleviate the effect of noise. Images w...

This paper shows a relationship between two different approximation techniques: the Support Vector Machines (SVM), proposed by V. Vapnik (1995), and a sparse approximation scheme that resembles the Basis Pursuit De-Noising algorithm (Chen, 1995; Chen, Donoho and Saunders, 1995). SVM is a technique which can be derived from the Structural Risk Minimization Principle (Vapnik, 1982) and can be use...

We study a central difference discretization of Rudin-Osher-Fetami model for image de-noising. We show that the discrete solution uk converges to the continuous solution u in L2 norm and a rate of convergence is given.

The studies to gather, systematize, scrutinize, and deduce numerical information from data is known as statistics. Min, max, mean, mode, midpoint, median, variance, standard deviation, covariance, histogram etc are the important image statistics used in various root level field of image processing and computer vision like Image enhancement [1-3], image restoration [2,3], image de-blurring [2], ...