ABSTRACT
In this paper, we present a novel study on the impact of lossy data compression on the metrological properties of holographic tomography reconstruction of the refractive index (RI). We use a spatial bandwidth-optimized compression procedure that leverages the properties of image plane off-axis holograms and standardized compression codecs, both widely applied in research and industry. The compression procedure is tested at multiple bitrates, for four different objects and against three reconstruction algorithms. The metrological evaluation is primarily done by comparison to the reconstruction from original data using the root-mean-squared error (RMSE). We show that due to differences between objects and different noise sensitivities of the reconstruction algorithms, the rate-distortion behaviour varies, but in most cases allows for the compression below 1 bit per pixel, while maintaining an RI RMSE less than 10-4.
ABSTRACT
Image plane off-axis holograms (IP-OAH) are the most common data captured in digital holographic microscopy and tomography. Due to increasing storage and data transmission requirements, lossy compression of such holograms has been subject of earlier investigations. However, hologram compression can not be allowed to hinder the metrological capabilities of the measurement technique itself. In this work, we present lossy and lossless IP-OAH compression approaches that are based on conventional compression codecs, but optimized with regard to bandwidth of the signal. Both approaches outperform respective conventional codecs, while the lossy approach is shown to uphold the accuracy of holographic phase measurements.