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不同插值算法的光场重聚焦分析
引用本文:常青,赵双明.不同插值算法的光场重聚焦分析[J].应用光学,2020,41(3):482-489.
作者姓名:常青  赵双明
作者单位:武汉大学 遥感信息工程学院,湖北 武汉 430079
基金项目:北京市科技计划(Z191100004319001)
摘    要:光场数据重聚焦包括空间域重聚焦和频域重聚焦两种方法,在重聚焦过程中均需要进行插值计算,重聚焦精度与插值精度密切相关,而插值算法的复杂度会影响计算效率。在实际大量图像处理中,在重聚焦效果满足精度要求的前提下选择计算效率最高的方法,其中,插值精度对频域影响远大于空间域。介绍了空间域重聚焦和频域重聚焦的原理,以及传统3种插值方法和sinc函数插值法,分别用不同的插值方法对这两种重聚焦方法进行实验,比较其重聚焦效果并计算其效率。实验结果表明,在实际应用中为了满足计算效率的需求,在满足精度要求情况下,空间域重聚焦采用线性插值法最佳,频域采用采样半径为2像素的sinc插值最佳。对同一幅影像多次重聚焦时,频域方法优于空间域方法。

关 键 词:插值算法    光场相机    空间域重聚焦    频域重聚焦    sinc插值
收稿时间:2019-11-22

Light field refocusing analysis of different interpolation algorithms
Institution:School of Remote Sensing Information Engineering, Wuhan University, Wuhan 430079, China
Abstract:The light field data refocusing includes spatial domain refocusing and frequency domain refocusing. In the process of the refocusing, the interpolation calculation is needed, the refocusing precision is closely related to the interpolation precision, and the computational efficiency can be affected by the complexity of the interpolation algorithm. In the actual large amount of the image processing, the method with the highest computational efficiency is selected under the premise that the refocusing effect satisfies the accuracy requirement, and wherein the interpolation accuracy has a much greater influence on the frequency domain than the spatial domain. The principle of the spatial domain refocusing and the frequency domain refocusing, as well as the traditional three interpolation methods and the sinc function interpolation method were introduced. Different interpolation methods were used to experiment this two refocusing methods to compare their refocusing effect and calculate their efficiency. The experimental results show that in order to meet the requirement of the computational efficiency in actual applications, the linear interpolation method is the best method to optimize the spatial domain refocusing in the case of meeting the accuracy requirement, and the sinc interpolation with the sampling radius of 2 is optimal in the frequency domain. When the same image is refocused for multiple times, the frequency domain method is superior to the spatial domain method.
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