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Compression of digital holograms of three-dimensional objects using the wavelet transform

机译：利用小波变换压缩三维物体的数字全息图

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Wavelets are used extensively in image processing due to the localized frequency information that can be conveyed by the wavelet transform. This and other characteristics of wavelet transforms can be exploited very effectively for the compression of images. We apply the wavelet transform to digital holograms of three-dimensional objects. Our digital holograms are complex-valued signals captured using phase-shift interferometry. Speckle gives them a white noise-like appearance with little correlation between neighboring pixels. In our analyses we concentrate on the discrete wavelet transform and Haar dyadic bases. We achieve compression through quantization of the wavelet transform coefficients. We quantize the discrete wavelet coefficients in each of the subbands depending on the dynamic range of the coefficients in that subband. Finally, we losslessly encode these subbands to quantify the high compression ratios achieved. We outline the three issues that need to be dealt with in order to improve the compression ratio of wavelet based techniques for particular applications as (ⅰ) determining a good criterion for ascertaining the coefficients that have to be retained, (ⅱ) determining a quantization strategy and quantization error appropriate to one's particular application, and (ⅲ) compression of the bookkeeping data.
机译：由于小波变换可以传达局部的频率信息，因此小波被广泛用于图像处理。小波变换的这个和其他特征可以非常有效地用于图像压缩。我们将小波变换应用于三维物体的数字全息图。我们的数字全息图是使用相移干涉术捕获的复数值信号。斑点使它们具有类似白噪声的外观，相邻像素之间几乎没有相关性。在我们的分析中，我们专注于离散小波变换和Haar二进位基数。我们通过对小波变换系数进行量化来实现压缩。我们根据每个子带中系数的动态范围对每个子带中的离散小波系数进行量化。最后，我们对这些子带进行无损编码，以量化获得的高压缩率。我们概述了在特定应用中为提高基于小波技术的压缩率而需要处理的三个问题，因为（ⅰ）确定确定必须保留的系数的良好标准，（ⅱ）确定量化策略以及适合个人特定应用的量化误差，以及（ⅲ）记账数据的压缩。

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