Terrillon J C
Appl Opt. 1996 Apr 10;35(11):1879-93. doi: 10.1364/AO.35.001879.
I propose a new method that ensures efficient rotation-invariant pattern recognition in the presence of signal-dependent noise by combining the application of rotation-invariant correlation filters with preprocessing of the noisy input images. The preprocessing uses local suboptimal estimators derived from estimation theory and implies an a priori knowledge of a model describing the noise source. The image noise sources considered are speckle and film-grain noise. Pour different metrics are used to analyze the correlation performance of the circular-harmonic filter, the phase-only circular-harmonic filter, and the binary phase-only circular-harmonic filter, with and without a preprocessing. Computer simulations show that signal-dependent noise can seriously degrade the performance of the phase-only circular-harmonic filter and the binary phase-only circular-harmonic filter. The most severe indication of correlation-performance degradation is the occurrence of false alarms in 15% to 20% of noise realizations of the correlation. Preprocessing increases the correlation-peak signal-to-noise ratio significantly and reduces the false-alarm probability by one to two orders of magnitude.
我提出了一种新方法，该方法通过将旋转不变相关滤波器的应用与有噪声输入图像的预处理相结合，确保在存在信号相关噪声的情况下实现高效的旋转不变模式识别。预处理使用从估计理论导出的局部次优估计器，并隐含描述噪声源的模型的先验知识。所考虑的图像噪声源是散斑噪声和胶片颗粒噪声。使用四种不同的指标来分析循环谐波滤波器、纯相位循环谐波滤波器和二元纯相位循环谐波滤波器在有无预处理情况下的相关性能。计算机模拟表明，信号相关噪声会严重降低纯相位循环谐波滤波器和二元纯相位循环谐波滤波器的性能。相关性能下降最严重的表现是在15%至20%的相关噪声实现中出现误报。预处理显著提高了相关峰值信噪比，并将误报概率降低了一到两个数量级。
