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Edge detection in noisy images using wavelet transform

机译:小波变换在噪声图像中的边缘检测

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摘要

In this paper, we present edge detection technique based on wavelet transform for noisy images. Edge detection is basic and significant technique in medicine and image processing. The conventional approaches to edge detection fail when the noise is present in images. Noise can be effectively reduced using wavelet transform without any significant loss in the image quality. Unlike canny edge detection in which the first step is image smoothing by a Gaussian filter to reduce the effect of noise and next step is edge detection. In wavelet these two steps are combined into a single step and thus wavelet based techniques are computationally more efficient and it uses multiresolution technique It is experimentally proved that the wavelet based edge detection gives better result than traditional techniques for noisy images.
机译:在本文中,我们提出了基于小波变换的噪声图像边缘检测技术。边缘检测是医学和图像处理中的基础和重要技术。当图像中存在噪声时,传统的边缘检测方法将失败。使用小波变换可以有效降低噪声,而不会显着降低图像质量。与Canny边缘检测不同,Canny边缘检测的第一步是通过高斯滤波器对图像进行平滑处理,以减少噪声的影响,而下一步是边缘检测。在小波中,这两个步骤被组合为一个步骤,因此基于小波的技术在计算上更加有效,并且使用了多分辨率技术。实验证明,基于小波的边缘检测对于噪点图像的检测效果要优于传统技术。

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