An Image Edge Detection Algorithm Based on One-Dimensional Discrete Wavelet Signal-Noise Separation

X. Li, X. Zhao
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引用次数: 1

Abstract

By using wavelet transform modulus maxima method to detection image edge, edge details are easily smoothed out in the large scale analysis and related parameters great influenced by the noise is not easy to extract in traditional small scale analysis. To solve this problem, this paper proposes a method based on one-dimensional discrete wavelet image edge detection. This algorithm decompose image into one-dimensional signal, making signal-noise separation with one-dimensional discrete wavelet, and detect the edge of de-noised signal's high frequency components. The article has experimented the multiple vehicle detection in real scene for many times, and the result shows that this algorithm solved the problem that exist in wavelet transform modulus maxima method to test image edges in small scale analysis, restraining noise better, and had higher precision in edge localization.
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基于一维离散小波信噪分离的图像边缘检测算法
利用小波变换模极大值法检测图像边缘,在大尺度分析中边缘细节容易平滑,而在传统的小尺度分析中受噪声影响较大的相关参数不易提取。为了解决这一问题,本文提出了一种基于一维离散小波图像边缘检测的方法。该算法将图像分解为一维信号,用一维离散小波进行信噪分离,并检测去噪信号高频成分的边缘。本文对真实场景中的多车检测进行了多次实验,结果表明,该算法解决了小波变换模极大值法在小尺度分析中检测图像边缘时存在的问题,更好地抑制了噪声,边缘定位精度更高。
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