Abstract
Digital image processing has been playing an important role in many areas and different fields for decades. Edge detection, as a crucial technique of digital image processing, forms the foundation of many digital image processing techniques. In this paper, we propose an image edge detection method based on Haar Wavelet Transform and compare this method with several up-to-date edge detection methods. First, we preprocess the data by extracting the Y channel of the image. Second, we utilize an adaptive wiener filter for the noise removal. Final, we apply Haar Wavelet Transform and obtain the final output image by steps Absolute magnitude image and Otsu Threshold Segmentation. Then, we carry out a performance evaluation based on Receiver operating characteristic (ROC) curve. Based on the simulation results, we conclude that the proposed edge detection method surpasses several existing methods in clarity and denoising degree.
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