基于PCA的相机响应函数特征化方法研究

A Characteristic Method of Camera Response Function(CRF) Based on PCA

  • 摘要: 响应函数是CCD和CMOS成像器件的重要特性之一. 传统的响应函数测试方法存在对实验条件要求苛刻、测试速度慢、人工成本高等不足. 基于201条已有的响应函数曲线,采用PCA方法提取相机响应函数空间中对应5个最大特征值的特征向量,并用这5个特征向量的线性组合表达已有的201条响应函数曲线,取得了较高的精度. 对4种不在响应函数库中的数码相机响应函数进行了特征向量表达,也获得了较高的精度,证明相机响应函数空间特征向量能够表达任意相机的响应函数.

     

    Abstract: Response function is one of the important characteristics of CCD and CMOS. Traditional measure method of response function needs to fulfill strict measurement conditions, and has the shortcomings that low measurement efficiency and high measurement cost. This paper uses PCA method to compute 5 eigenvectors corresponding to 5 maximum eigenvalues of the response function space based on 201 existing response functions. Expressing the existing response functions by the linear combination of the 5 eigenvectors, a rather accurate result was achieved. 4 type of digital cameras' response functions which were not included in the 201 existing response functions were expressed by the eigenvectors of camera response functions' space. The result is rather accurate which proves the effectiveness of the method.

     

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