Detection of high frequency regions in multiresolution

We propose a method for the detection of high frequency regions using multiresolution analysis and orientation tensors. A scalar field representing multiresolution edges is obtained. Local maxima of this scalar space indicate regions having coincident detail vectors in multiple scales of a wavelet decomposition. This is useful for finding edges, textures, collinear structures and salient regions for computer vision methods. The image is decomposed into several scales using the discrete wavelet transform (DWT). The resulting detail spaces form vectors indicating intensity variations which are adequately combined using orientation tensors. The multivariate data of the resulting tensor field provides fair estimations of high frequency regions. Using these tensors, a positive scalar is computed for each original image pixel. Our results show that this descriptor indicates areas having relevant intensity variation in multiple scales.