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Journal Article Quantization of Dynamic Speckle Patterns with Spatially Varying Statistics
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Authors
Elena Stoykova, Dimana Nazarova, Lian Nedelchev, Blaga Blagoeva, Nataliya Berberova, Keehoon Hong, Joongki Park
Issue Date
2021-02
Citation
Applied Optics, v.60, no.4, pp.155-165
ISSN
1559-128X
Publisher
Optical Society of America (OSA)
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1364/AO.405991
Abstract
Raw data compression is mandatory for monitoring of processes by dynamic speckle analysis when two-dimensional activity maps are built by pointwise statistical processing of correlated speckle patterns formed on the surface of diffusely reflecting objects under laser illumination. Coarse quantization of speckle patterns enables storage and transfer of a huge amount of images, but it may be inefficient at spatially varying speckle statistics, such as for patterns recorded at non-uniform illumination or reflectivity. We prove efficacy of coarse quantization of the raw speckle data with varying statistics for a normalized algorithm by simulation and a polymer drop drying experiment. Both uniform and non-uniform quantization are proposed for treating such data. Decreasing the bit depth from 8 to 3 is possible without worsening the quality of the activity map.
KSP Keywords
Activity map, Coarse Quantization, Drop drying, Dynamic speckle, Non-uniform Illumination, Non-uniform quantization, Polymer drop, Raw Data, Statistical processing, bit depth, data compression