Image fusion is defined as the process of combining two or more different images into a new single image retaining important features from each image with extended information content. There are two approaches to image fusion, namely Spatial Fusion and Transform fusion. In Spatial fusion, the pixel values from the source images are directly summed up and taken average to form the pixel of the c...

Image fusion is defined as the process of combining two or more different images into a new single image retaining important features from each image with extended information content. There are two approaches to image fusion, namely Spatial Fusion and Transform fusion. In Spatial fusion, the pixel values from the source images are directly summed up and taken average to form the pixel of the c...

Rob A. Zuidwijk CWI E-mail: [email protected] Url: http://www.cwi.nl/cwi/projects/wavelets.html November 6, 1997 Abstract In this lecture, the continuous wavelet transform will be discussed and some attention will be given to the discrete wavelet transform. Finally, wavelet transforms on multidimensional data will be considered. The set-up of the lecture is as follows: 1. The continuous wavelet t...

In the fluorescence detection system, noise will affect the sensitivity of the system. The method using Stationary Wavelet Transform to de-noise fluorescence signals based on adaptive wavelet entropy is studied. The de-noising effects of dbN families are compared, and then the db7 wavelet is chosen as the optimal wavelet. The noised fluorescence signal is decomposed at 5 levels via Discrete Wav...

This paper presents a new multi-sensor data fusion method based on the combination of wavelet transform (WT) and extended Kalman filter (EKF). Input data are first filtered by a wavelet transform via Daubechies wavelet “db4” functions and the filtered data are then fused based on variance weights in terms of minimum mean square error. The fused data are finally treated by extended Kalman filter...

The purpose of this study was to identify the formation interfaces from geophysical well log data using the wavelet transform, and a combination of the wavelet transform and the Fourier transform methods. In the wavelet transform method, the identification of formation interfaces is based on the wavelet coefficients from the wavelet transform of spontaneous potential (SP) log and gamma ray (GR)...

This paper presents an algorithm for medical 3D image denoising and segmentation using redundant discrete wavelet transform. First, we present a two stage denoising algorithm using the image fusion concept. The algorithm starts with globally denoising the brain images (3D volume) using Perona Malik’s algorithm and RDWT based algorithms followed by combining the outputs using entropy based fusio...

Image fusion is defined as the process of combining tw o or more different images into a new single image retaining important features from each image w ith extended information content. There are two approaches to image fusion, namely Spatial Fusion and Transform fusion. In Spatial fusion, the pixel values from the source images are directly summed up and taken average to form the pixel of the...

In this chapter, we illustrate the properties of the continuous shearlet transform with respect to its ability to describe the set of singularities of multidimensional functions and distributions. This is of particular interest since singularities and other irregular structures typically carry the most essential information in multidimensional phenomena. Consider, for example, the edges of natu...

Quality control of textile products is an important stage in textile industries. To this end, the conventional method in fault detection is human inspection. In the present work, Wavelet transform was applied on images of simple circular knitted fabrics to diagnose five regular defects. The results showed that the method applied was accurate and fast in addition to being capable of determining ...