in this paper, we present an edge detection method based on wavelet transform and hessian matrix of image at each pixel. many methods which based on wavelet transform, use wavelet transform to approximate the gradient of image and detect edges by searching the modulus maximum of gradient vectors. in our scheme, we use wavelet transform to approximate hessian matrix of image at each pixel, too. ...

corrosion of reinforcing steel and other embedded metals is the main cause of severe deterioration in reinforced concrete structures which subsequently imposes adverse effects on ultimate and serviceability limit state performance of the whole structure. in this paper, a new corrosion detection method for reinforced concrete beams, based on wavelet analysis is presented. to evaluate the capabil...

Image fusion is one of the most useful term related to digital image processing, computer vision and medical imaging. The objective of image fusion is to extract the useful information from several images into a single image. Recently, more research has been done on wavelet based image fusion methods for medical application. Wavelet transform is useful for objects with point singularities and a...

The occurrence of cycle slips is a major limiting factor for achievement of sub-decimeter accuracy in positioning with GPS (Global Positioning System). In the past, several authors introduced a method based on different combinations of GPS data together with Kalman filter to solve the problem of the cycle slips. In this paper the same philosophy is used but with discrete wavelet transforms. For...

Dizziness and or unsteadiness, associated with episodes of loss of balance, are frequent complaints in those suffering from persistent problems following a whiplash injury. Research has been inconclusive with respect to possible aetiology, discriminative tests and analyses used. The aim of this pilot research was to identify the test conditions and the most appropriate method for the analysis o...

Texture classification is an important and challenging problem in many image processing applications. While convolutional neural networks (CNNs) achieved significant successes for image classification, texture classification remains a difficult problem since textures usually do not contain enough information regarding the shape of object. In image processing, texture classification has been tra...

Abstract Studies of the low-frequency variabilities key climate variables are often handicapped by limited length available instrumental observations. To tackle this, use a set historical flood/drought index (FDI) spanning from AD 1470 to 2000 for 120 sites in China has been made investigate multiscale temporal variability annual precipitation applying wavelet methods. The analyses reveal oscil...

An exploration of the wavelet transform as applied to daily river discharge records demonstrates its strong potential for quantifying stream ̄ow variability. Both periodic and non-periodic features are detected equally, and their locations in time preserved. Wavelet scalograms often reveal structures that are obscure in raw discharge data. Integration of transform magnitude vectors over time yi...