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引用次数: 1

摘要

近年来,利用光学相关器进行特征提取显示出良好的边缘增强潜力。因此,我们研究了拉普拉斯算子和索贝尔算子在多目标特征提取中的性能。通过功率谱减法技术去除零阶和虚警项等不需要的项。同时,在联合小波变换相关器中引入分离目标面和参考面方法,使磁光空间光调制器的空间带宽积最大化。提出了一种经济高效的实时光学相关光电硬件。对两种情况进行了计算机模拟,验证了上述结果;在无噪声和重叠的加性噪声破坏情况下使用拉普拉斯算子和索贝尔算子。拉普拉斯算子可以用较少的步骤实现,并且最适合于实时关联。Sobel算子产生更好的边缘信息,对噪声损坏有更高的容忍度,但需要额外的相关步骤,代价是更多的计算时间。
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Efficient edge enhancement using real time optical correlation
In recent years, feature extraction using an optical correlator shows promising edge enhancement potential. Hereby, we investigate the performance of the Laplace and Sobel operators in feature extraction for multiple targets. The undesired terms such as the zero-order and false alarm terms are removed by the power spectrum subtraction technique. Also, the separated target and reference planes method is incorporated into the joint wavelet transform correlator to maximize the space-bandwidth product of a magneto-optic spatial light modulator. A cost effective and efficient optoelectronic hardware is proposed for realtime optical correlation. The aforementioned result is verified by computer simulation for both cases; in noise free and in overlapping additive noise corruption situations using both the Laplace and Sobel operators. The Laplace operator could be implemented with lesser steps and is most appropriate for real-time correlation. The Sobel operator yields better edge information and has higher tolerance to noise corruption but required additional correlation steps at the expense of more computation time.
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