Abstract. We propose a method for the assessment and visualization of high frequency regions of a multiresolution image. We combine both orientation tensor and multiresolution analysis to give a scalar descriptor of high frequency regions. High values 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 combined using orientation tensors. A high frequency scalar descriptor is then obtained from the resulting tensor for each original image pixel. Our results show that this descriptor indicates areas having relevant intensity variation in multiple scales.
For mask signature matching in the case of alternating phase-shifting mask it is shown that it is can be achieved using matching of aerial imaging. This is in contrast to the traditional approach of manufacturing an identical copy of the reference mask. Beside description of the method AIMS and wafer data are shown that proof its successful application on a product mask.
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