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...

a cochlear implant is an implanted electronic device used to provide a sensation of hearing to a person who is hard of hearing. the cochlear implant is often referred to as a bionic ear. this paper presents an undecimated wavelet‑based speech coding strategy for cochlear implants, which gives a novel speech processor. the undecimated wavelet packet transform (uwpt) is computed like the wavelet ...

As any process in Nature, seismic records are affected by noise that the analyst would want to eliminate. One of the most common techniques used to minimise this noise effect is the application of linear filters, which reduce the bandwidth of the signal. This method is based on the Fourier Transform, and therefore any perturbation on the coefficients affects the entire record. We have developed...

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...

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...

ABSTIUCT In our previous work, we introduced a new class of nonstationary stochastic processes whose spectral representation is associated with the wavelet transforms and established a mathematical framework for the analysis of such processes 111. We refer to these processes as uffine stptionary processes. These processes are indexed by the affine p u p , or ax+b group, which can be though of a...

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...

Nonlinearities are often encountered in the analysis and processing of real-world signals. Most existing approaches to nonlinear signal processing characterize the nonlinearity in the time domain or frequency domain. In fact, there are good reasons for characterizing nonlinearity using more general signal representations like the wavelet expansion. Wavelet expansions often provide very concise ...

In this paper, a method of super-resolution image reconstruction based on wavelet transform and edge-directed interpolation is put forward. Firstly the low resolution image is decomposed by the stationary wavelet transform; meanwhile, the image obtained from edge-directed interpolation is decomposed by discrete wavelet transform, then the three high frequency sub bands obtained through stationa...