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Edge detection is one of the most commonly used operations in image analysis. Most algorithms contain two basic steps: denoise and derivative computing. We apply kernel regression to remove noise and to get gray-level and derivative intensity surface of images. We explore the Nadaraya-Watson kernel regression which conquers the more negative impact caused by noises for derivative computing than general...
The traditional wavelet edge detection algorithm doesn't ideal processing effects for the salt & pepper noised images. In allusion to this shortcoming, an improved wavelet multi-scale edge detection algorithm is proposed in this paper. Morphology is assimilated into the wavelet detection, and an objective data evaluation is given. Compared with the traditional method, the related coefficient of...
In this paper, we propose a design method for directional selection in the 2-Dimensional Complex Wavelet Packet Transform. Previous 2-Dimensional Complex Discrete Wavelet Transforms break up direction components, but the number of directions is small, and the directions and resolutions are fixed. So, they are not flexible enough. In this study, we propose a new design method that can detect desirable...
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