Image fusion is defi ned 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 and three levels namely pixel, feature and region level. In spatial fusion, the pixel values from the source images are direct...

Besides many advantages of wavelet transform, it has several drawbacks, e.g. ringing, shift variance, aliasing and lack of directionality. Some of them can be eliminated by using wavelet packet transform, stationary wavelet transform, complex wavelet transform, adaptive directional lifting-based wavelet transform, or adaptive wavelet filter banks that use either L2 or L1 norm. This paper contai...

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 ...

Introduction: One of the major problems in the development of nuclear medicine images is the presence of noise. The noise level in nuclear medicine images is usually reduced by the analysis of imaging data in a Fourier transform environment. The main drawback of this environment belongs to low signal to noise ratio in high frequencies because removing noise frequencies may remove data and times...

Abstrac t This paper presents a method for locating and measuring the size of cracks in beams by time of flight (ToF) of ultrasonic wave. The echo detected was processed using the stationary wavelet transform and the Hilbert transform. The accuracy of the information obtained from the processed signal depends on the selected mother wavelet. To select the best mother wavelet for signal processin...

spectral decomposition is a powerful tool for analysis of seismic data. fourier transform determines the frequency contents of a signal. but for analysis of non-stationary signals, 1-d transform to frequency domain is not sufficient. in early years, transforming of seismic traces into time and frequency domain was done via windowed fourier transform, called a short time fourier transform (stft)...