Contourlet transform is an efficient directional multiscale decomposition of images that combines the Laplacian pyramid (LP) with directional filter banks (DFBs). The LP decomposes the input image into multiple scales, whereas the DFBs applied on bandpass images of the pyramid yields directional localization. Similar to wavelets in 1-D, the key feature of contourlets is that they can quickly “f...

abstract background: a computer aided diagnosis system was established using the wavelet transform and neural network to differentiate malignant from benign in a   group of patients with histo-pathologically proved breast lesions based on the data derived independ­ently from time-intensity profile.   materials and methods: the per­formance of the artificial neural network (ann) was evaluated us...

Texture represents spatial or statistical repetition in pixel intensity and orientation. Brain tumor is an abnormal cell or tissue forms within a brain. In this paper, a model based on texture feature is useful to detect the MRI brain tumor images. There are two parts, namely; feature extraction process and classification. First, the texture features are extracted using techniques like Curvelet...

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 ...

introduction: spect is a diagnostic imaging technique the main disadvantage of which is the existence of poisson noise. so far, different methods have been used by scientists to improve spect images. the wavelet transform is a new method for de-noising which is widely used for noise reduction and quality enhancement of images. the purpose of this paper is evaluation of noise reduction in spect ...