We have built several networks of inferior olive (IO) model neurons to study the emerging spatio-temporal patterns of neuronal activity. The degree and extent of the electrical coupling, and the presence of stimuli were the main factors considered in the IO networks. The network activity was analyzed using a discrete wavelet transform which provides a quantitative characterization of the spatio...

Fabric defect detection is one of the indispensible units in the manufacturing industry to maintain the quality of the end product. Wavelet transform is well suited for quality inspection application due to its multi-resolution representation and to extract fabric features. This paper presents the comparison of three wavelet based models. These models include Tree structured wavelet transform, ...

A few different approaches exist for computing undecimated wavelet transform. In this work we construct three undecimated schemes and evaluate their performance for image noise reduction. We use standard wavelet based de-noising techniques and compare the performance of our algorithms with the original undecimated wavelet transform, as well as with the decimated wavelet transform. The experimen...

Fourier transform is applied to detect the direction of stripe noise before de-noising, which is advantageous for selecting the corresponding detail coefficients for threshold quantization after stationary wavelet transform. Depending on the direction of stripe noise, the corresponding detail coefficients contain stripe noise need to be removed, while retaining the approximate coefficients and ...

Wavelet transforms have become one of the most important and powerful tool of signal representation. Nowadays, it has been used in image processing, data compression, and signal processing. This paper will introduce the basic concept for Wavelet Transforms, the fast algorithm of Wavelet Transform, and some applications of Wavelet Transform. The difference between conventional Fourier Transform ...

Image denoising using wavelet transform has been successful as wavelet transform generates a large number of small coefficients and a small number of large coefficients. Basic denoising algorithm that using the wavelet transform consists of three steps – first computing the wavelet transform of the noisy image, thresholding is performed on the detail coefficients in order to remove noise and fi...

In this paper a watermarking method using hybrid wavelet transform and SVD is proposed. Hybrid wavelet transform generated from two different orthogonal transforms is applied on host and SVD is applied to watermark. The transforms used for hybrid wavelet transform generation are DCT, Walsh, Haar and DKT. First component transform used in generation of hybrid wavelet transform corresponds to glo...

This term project report introduces the well-know Gabor wavelet transform and its applications. Wavelet transform could extract both the time (spatial) and frequency information from a given signal, and the tunable kernel size allows it to perform multi-resolution analysis. Among kinds of wavelet transforms, the Gabor wavelet transform has some impressive mathematical and biological properties ...

An orthogonal m-band discrete wavelet transform has an O(m 2) complexity. In this paper we present a fast implementation of such a discrete wavelet transform. In an orthonormal m-band wavelet system, the vanishing moments (which corresponds to the approximation order and smoothness) and orthogonality conditions are imposed on the scaling lter (or lowpass lter) only. Given a scaling lter, one ca...

An effective rotation and scale invariant log-polar wavelet texture feature for image retrieval was proposed. The feature extraction process involves a log-polar transform followed by an adaptive row shift invariant wavelet packet transform. The log-polar transform converts a given image into a rotation and scale invariant but rowshifted image, which is then passed to the adaptive row shift inv...