利用小波系数的相关性提取噪声图像边缘
Detecting Noisy Image Edge Based on Correlation of the Multi-Level Wavelet Coefficients
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摘要: 首先,对噪声图像作多层次小波分解,得到对应的多个层次的小波系数,并利用相邻各层次小波系数的相关性质构建滤波器;然后,利用该滤波器对平滑小波系数进行滤波操作,去除噪声影响,得到滤波图像;最后,对滤波图像阈值化以得到噪声图像的边缘图.实验表明,该方法比传统的图像边缘提取方法具有更好的抗噪性能.Abstract: The noisy image is first decomposed into multi-level wavelet to obtain the corresponding coefficients, and a filter is constructed by correlating the multi-level wavelet coefficients. Then, the filter is applied to an original level with smoothed wavelet coefficients to get noise-free image. Finally, the filtered image is thresholded to produce the edge image. Experiment result shows that this approach can get rid of much more noise than conventional edge detection methods.
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