Image segmentation is one of the vital steps in Image processing. It is a challenging task in segmenting MRI(Magnetic Resonance Imaging) images because these images have no linear features. But MRI images provide high quality when compared to any other imaging techniques, so it is best suited for clinical diagnosis, biomedical research, etc. This paper presents a novel approach for segmenting M...

In this paper, a novel road extraction method using Stationary Wavelet Transform is proposed. To detect road features from color aerial satellite imagery, Mexican hat Wavelet filters are used by applying the Stationary Wavelet Transform in a multiresolution, multi-scale, sense and forming the products of Wavelet coefficients at a different scales to locate and identify road features at a few sc...

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 ...

introduction: an efficient method of tomographic imaging in nuclear medicine is positron emission tomography (pet). compared to spect, pet has the advantages of higher levels of sensitivity, spatial resolution and more accurate quantification. however, high noise levels in the image limit its diagnostic utility. noise removal in nuclear medicine is traditionally based on fourier decomposition o...

the record of human brain neural activities, namely electroencephalogram (eeg), is generally known as a non-stationary and nonlinear signal. in many applications, it is useful to divide the eegs into segments within which the signals can be considered stationary. combination of empirical mode decomposition (emd) and hilbert transform, called hilbert-huang transform (hht), is a new and powerful ...

The main objective of super-resolution (SR) imaging is to reconstruct a high-resolution (HR) image of a scene from one or more low-resolution images of the scene. In resolution enhancement of images, the main loss is on the high frequency components (edges) of the image. This is due to the smoothing caused by interpolation. Hence in order to enhance the quality of the super resolved image, pres...