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Optical correlation recognition of infrared target based on wavelet multi-scale product

机译:基于小波多尺度积的红外目标光学相关识别

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As one of the most successful optical correlation recognizers, hybrid optoelectronic joint transform correlator (HOJTC) has received more and more attraction than the purely electronic way in the field of target detection and recognition. It primarily because that HOJTC has the advantages of optics as well as those of electronics. This kind of combination determines that the performance of HOJTC is closely related to optical configuration of system and digital image processing technology. For the stability of optical part, a lot of efforts concerning image processing methods have been made in recent years for improving the power of recognition of HOJTC. Edge contours play a decisive role in target detection. In order to obtain adequate contour feature of target, the solution of edge extraction based on wavelet multi-scale product is proposed. Normalized maximum and argument of each point could be defined utilizing wavelet coefficient of image. Both of them contain the relation of coefficient product between each scale. Edge points synthesized the information of multi-scale are extracted by searching local maxima along the direction of gradient. The way adopted fully exploited the character of multi-resolution of wavelet. Simulation experiments and optical experiments indicate that the energy of correlation peaks is obviously enhanced after the original image is processed by wavelet multi-scale product, and it successfully realizes detection and recognition of infrared target.
机译:作为最成功的光学相关识别器之一,混合光电联合变换相关器(HOJTC)在目标检测和识别领域比纯电子方式具有越来越多的吸引力。这主要是因为HOJTC具有光学和电子方面的优势。这种结合决定了HOJTC的性能与系统的光学配置和数字图像处理技术密切相关。为了光学部件的稳定性,近年来已经进行了许多与图像处理方法有关的努力以提高HOJTC的识别能力。边缘轮廓在目标检测中起决定性作用。为了获得足够的目标轮廓特征,提出了基于小波多尺度积的边缘提取方法。可以利用图像的小波系数来定义每个点的归一化最大值和自变量。两者都包含每个标度之间的系数积关系。通过沿梯度方向搜索局部最大值来提取综合了多尺度信息的边缘点。采用的方法充分利用了小波多分辨率的特点。仿真实验和光学实验表明,利用小波多尺度乘积处理原始图像后,相关峰的能量明显增强,成功实现了红外目标的检测与识别。

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