Naughton Thomas J, Frauel Yann, Javidi Bahram, Tajahuerce Enrique
National University of Ireland, Department of Computer Science, Maynooth, Republic of Ireland.
Appl Opt. 2002 Jul 10;41(20):4124-32. doi: 10.1364/ao.41.004124.
We present the results of applying lossless and lossy data compression to a three-dimensional object reconstruction and recognition technique based on phase-shift digital holography. We find that the best lossless (Lempel-Ziv, Lempel-Ziv-Welch, Huffman, Burrows-Wheeler) compression rates can be expected when the digital hologram is stored in an intermediate coding of separate data streams for real and imaginary components. The lossy techniques are based on subsampling, quantization, and discrete Fourier transformation. For various degrees of speckle reduction, we quantify the number of Fourier coefficients that can be removed from the hologram domain, and the lowest level of quantization achievable, without incurring significant loss in correlation performance or significant error in the reconstructed object domain.
我们展示了将无损和有损数据压缩应用于基于相移数字全息术的三维物体重建与识别技术的结果。我们发现,当数字全息图以实部和虚部分别数据流的中间编码形式存储时,可预期获得最佳的无损(莱姆佩尔 - 齐夫、莱姆佩尔 - 齐夫 - 韦尔奇、哈夫曼、伯罗斯 - 惠勒)压缩率。有损技术基于子采样、量化和离散傅里叶变换。对于不同程度的散斑减少,我们量化了可从全息图域中去除的傅里叶系数数量,以及可实现的最低量化级别,同时不会在相关性能上产生显著损失或在重建物体域中产生显著误差。