Abstract
In this paper, we propose a novel wavelet edge detection algorithm for noisy images. The proposed edge detection method works efficiently on images influenced by noise and is able to differentiate between noise and real edges, thus detecting the actual edges. Classical edge detectors like Roberts, Sobel, Prewitt and Laplacian operators fail to detect edges in noisy images. To evaluate the vulnerability of the proposed edge detector to noise, the PSNR of proposed edge detector on image with Gaussian noise is compared with Canny, Log, and Multiscale edge detectors and it is found that our method outperforms the classical edge detectors very efficiently.
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