Research on FAF joint tranform correlator based on morphological processing of input image
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摘要:为改善联合变换相关器的相关输出结果,提高图像识别能力,提出了一种将输入面形态学处理与功率谱面FAF处理相结合的方法。首先,介绍了经典联合变换相关器的基本原理;其次,针对联合变换相关器的缺点和不足,提出将输入面形态学预处理和功率谱FAF处理相结合,以改进经典联合变换相关器的相关输出性能;最后,详细分析了上述改进型联合变换相关器的参数选取问题。实验结果表明:当参数选择为 、 时,相关峰很尖锐,峰值为 ,比传统的联合变换相关器互相关峰值提高了 。将输入面形态学处理与功率谱面FAF处理相结合效果好于单独使用其中一种方法,极大地改善了传统联合变换相关器的目标识别能力。Abstract:A method based on the combination of input plane Mathematical Morphology processing and power plane FAF processing is proposed to improve the recognition ability of JTC. First, theory of classical JTC is introduced. Second, aiming at its disadvantage, the combination of input plane morphology processing and power spectrum plane FAF processing is used to improve the correlation output performance of JTC. Finally, The parameter of the proposed JTC are analyzed. Experimental results show that when the correlation peak is very sharpness. The peak value is , which is higher than classical JTC. Performance of the combination based method is better than that of any single method based JTC. Target detection ability is also improved by using the proposed JTC.
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