in this paper, we review novel techniques in the emerging field of spatiotemporal 4d pet imaging. we will discuss existing limitations in conventional dynamic pet imaging which involves independent reconstruction of dynamic pet datasets. various approaches that seek to attempt some or all of these limitations are reviewed in this work, including techniques that utilize iterative temporal smooth...

In this paper we present a comparative study on fusion of visual and thermal images using different wavelet transformations. Here, coefficients of discrete wavelet transforms from both visual and thermal images are computed separately and combined. Next, inverse discrete wavelet transformation is taken in order to obtain fused face image. Both Haar and Daubechies (db2) wavelet transforms have b...

In image compression, the wavelet transformation is a state-of-the-art component. Recently, wavelet packet decomposition has received quite an interest. A popular approach for wavelet packet decomposition is the near-best-basis algorithm using nonadditive cost functions. In contrast to additive cost functions, the wavelet packet decomposition of the near-best-basis algorithm is only suboptimal....

Face Recognition is used in order to ensure authentication in terms of feature verification. Techniques are defined to identify faces under different situations. This paper conducts a survey of techniques which are available for face detection. Recognition is possible in case features are extracted from the presented face images. For this purpose feature extraction mechanisms like discrete wave...

Wavelet decompositions of Raman spectra were investigated with respect to their usability for spike removal and denoising of the raw data. It could be shown that those operations should be performed sequentially. Suppression of spikes is not straightforwardly possible by wavelet transformation; however, the wavelet transform may be used to recognize the spikes by their first level detail coeffi...

We present a technique for facial feature localization using a two-level hierarchical wavelet network. The first level wavelet network is used for face matching, and yields an affine transformation used for a rough approximation of feature locations. Second level wavelet networks for each feature are then used to fine-tune the feature locations. Construction of a training database containing hi...

We present a technique for facial feature localization using a two-level hierarchical wavelet network. The first level wavelet network is used for face matching, and yields an affine transformation used for a rough approximation of feature locations. Second level wavelet networks for each feature are then used to fine-tune the feature locations. Construction of a training database containing hi...

Wavelet packet decomposition is used to investigate the time-varying characteristics of clinical EEG signals. On the basis of the nonstationary nature of clinical EEG rhythms, wavelet packet analysis is employed for designing filters with different frequency characteristics to detect 4 kinds of EEG rhythms. The coefficients of wavelet transformation corresponding to the rhythms are used to form...

Set Partioning in Hierarchical Trees (SPIHT) algorithm is a significant improvement of Embedded Zero Tree Wavelet (EZW) algoritm. It is based on the zero tree structure of EZW algorithm uses the smallest mean square error criterion.The most important wavelet coefficients are first encoded. It has got a good compression performance. The work is particularly targeted towards wavelet image compres...