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首页> 外文会议>RIAO/OPTILAS 2004 >Wavelet coefficients thresholding method applied to the correlation of noisy scenes
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Wavelet coefficients thresholding method applied to the correlation of noisy scenes

机译：小波系数阈值法在嘈杂场景关联中的应用

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摘要

The distortion of a signal due to noise contamination can be overcome by using a decomposition of the signal in a base of wavelets. If the decomposition coefficients are small compared with the noise, the scene is dominated by the distortion. On the contrary, if they are bigger in absolute value, the signal is stronger that the noise. A way of reconstructing an image with a lower level of noise is accomplished neglecting the coefficients which values are lower than a threshold, and replacing them by zero. In this work we present a method that applies the thresholding of the wavelet coefficients in order to perform pattern recognition of noisy scenes. The method could be implemented in optical processing by using a Vander Lugt correlator architecture operating with liquid crystal displays. The function to be recognized is decomposed in sub-bands based on the Gabor decomposition, in the frequency plane. Hard thresholding is performed and the threshold is g enerated w ith a ccurate support functions in the filter plane. The criterion for the thresholds election is chosen to optimize the signal to noise ratio in the output plane. Numerical simulations results are shown and comparisons with other filters are made.
机译：通过使用小波基中的信号分解，可以克服由于噪声污染引起的信号失真。如果分解系数与噪声相比较小，则场景将以失真为主。相反，如果它们的绝对值较大，则信号比噪声更强。忽略噪声值小于阈值的系数并将其替换为零，可以实现一种重构噪声较低的图像的方法。在这项工作中，我们提出了一种应用小波系数阈值的方法来执行嘈杂场景的模式识别。该方法可以通过使用与液晶显示器一起操作的范德鲁格特（Vander Lugt）相关器架构在光学处理中实现。在频率平面中，基于Gabor分解，在子带中分解要识别的功能。进行硬阈值处理，并在滤波器平面中使用精确的支持功能来生成阈值。选择用于阈值选择的标准以优化输出平面中的信噪比。显示了数值模拟结果，并与其他过滤器进行了比较。

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