Dual tree complex wavelet transform (DT-CWT) exhibits superiority of shift invariance, directional selectivity, perfect reconstruction (PR), and limited redundancy and can effectively separate various surface components. However, in nano scale the morphology contains pits and convexities and is more complex to characterize. This paper presents an improved approach which can simultaneously separ...

In this paper, we present variants of the Dual-Tree Complex Wavelet Transform (DT-CWT) in order to automatically classify endoscopic images with respect to the Marsh classi cation. The feature vectors either consist of the means and standard deviations of the subbands from a DT-CWT variant or of the Weibull parameter of these subbands. To reduce the e ects of di erent distances and perspectives...

The discrete wavelet transform (DWT) has proved very valuable in a large scope of signal processing problems. However, in many applications, it reaches its limitations, such as oscillations of the coefficients at a singularity, lack of directional selectivity in higher dimensions, aliasing and consequent shift variance. To overcome these problems, the complex wavelet transform (CWT) employs ana...

This study deals with the integration of medical images with multimodal Medical Image Fusion (MIF) problem, employing Improved DT-CWT (Dual Tree Complex Wavelet Transform) and a Discrete Optimization Method is to introduce a new approach to fuse panchromatic image and multi-spectral images. In image fusion, two approaches used namely Spatial and Transform. In Spatial fusion, it reduces structur...

The Wavelet transform has emerged over recent years as a key time frequency analysis and coding tool for the Electrocardiogram (ECG). Its ability to separate out pertinent signal components has led to a number of wavelet based techniques which supersede those based on traditional Fourier methods. It is interesting to note that researchers in the field of Wavelet transform tend to take an approa...

In this paper we present a new form of wavelet transform. Unlike the continuous wavelet transform (CWT) or discrete wavelet transform (DWT), the mother wavelet is chosen to be a discrete-time signal and wavelet coefficients are computed by correlating a given discrete-time signal with continuous dilations of the mother wavelet. The results developed are based on the definition of a discrete-tim...

This paper outlines a novel approach to wavelet based detection of epileptiform activity in the EEG. A special complex-valued wavelet filter is used in a continuous wavelet transform (CWT). The response of wavelet coefficients (WCs) to epileptiform discharges (EDs) is measured with respect to artifact-free background activity (BG). A detector based on the WCs of a single scale could operate at ...

In this paper, we propose an object recognition method for 2D objects using wavelet descriptors. The descriptors are derived from the continuous wavelet transform using the Mexican hat function as mother wavelet. In contrast to the other known methods we apply an angle function to describe object contours extracted as polygons. The contour extraction is based on the object oriented contour extr...

• wavelets are analysis tools for time series and images • as a subject, wavelets are − relatively new (1983 to present) − a synthesis of old/new ideas − keyword in 29, 826+ articles and books since 1989 (4032 more since 2005: an inundation of material!!!) • broadly speaking, there have been two waves of wavelets − continuous wavelet transform (1983 and on) − discrete wavelet transform (1988 an...

Image fusion aims to enhance the perception of a scene by combining important information captured by different sensors. Dual-Tree Complex Wavelet (DT-CWT) has been thouroughly investigated for image fusion, since it takes advantages of approximate shift invariance and direction selectivity. But it can only handle limited direction information. To allow a more flexible directional expansion for...