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Statistical investigation of the double random phase encoding technique

机译:双随机相位编码技术的统计研究

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摘要

The amplitude-encoding case of the double random phase encoding technique is examined by defining a cost function as a metric to compare an attempted decryption against the corresponding original input image. Forthe case when a cipher–text pair has been obtained and the correct decryption key is unknown, an iterative attack technique can be employed to ascertain the key. During such an attack the noise in the output field for an attempted decryption can be used as a measure of a possible decryption key’s correctness. For relatively small systems, i.e., systems involving fewer than 5x5 pixels, the output decryption of every possible key can be examined to evaluate the distribution of the keys in key space in relation to their relative performance when carrying out decryption. However, in order to do this for large systems, checking every single key is currently impractical. One metric used to quantify the correctness of a decryption key is the normalized root mean squared (NRMS) error. The NRMS is a measure of the cumulative intensity difference between the input and decrypted images. We identify a core term in the NRMS, which we refer to as the difference parameter, d. Expressions for the expected value (or mean) and variance of d are derived in terms of the mean and variance of the output field noise, which is shown to be circular Gaussian. These expressions assume a large sample set (number of pixels and keys). We show that as we increase the number of samples used, the decryption error obeys the statistically predicted characteristic values. Finally, we corroborate previously reported simulationsin the literature by using the statistically derived expressions.
机译:通过将成本函数定义为度量,以比较尝试的解密与相应的原始输入图像,来检验双随机相位编码技术的幅度编码情况。对于已获得密文对且未知解密密钥未知的情况,可以采用迭代攻击技术来确定密钥。在这种攻击期间,尝试解密的输出字段中的噪声可用作衡量可能的解密密钥正确性的方法。对于相对较小的系统,即,涉及少于5x5像素的系统,可以检查每个可能的密钥的输出解密,以便在执行解密时,根据密钥的相对性能来评估密钥在密钥空间中的分布。但是,为了对大型系统执行此操作,当前检查每个密钥都不可行。用于量化解密密钥正确性的一种度量是归一化均方根(NRMS)误差。 NRMS是输入图像和解密图像之间累积强度差的量度。我们在NRMS中标识一个核心术语,我们将其称为差异参数d。期望值(或均值)和d的方差的表达式是根据输出场噪声的均值和方差得出的,该输出场噪声表示为圆高斯。这些表达式假定样本集很大(像素和键的数量)。我们表明,随着我们增加使用的样本数量,解密错误将服从统计预测的特征值。最后,我们使用统计推导的表达式来证实文献中先前报道的模拟。

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