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학술지 Quantization of Dynamic Speckle Patterns with Spatially Varying Statistics
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저자
Elena Stoykova, Dimana Nazarova, Lian Nedelchev, Blaga Blagoeva, Nataliya Berberova, 홍기훈, 박중기
발행일
202102
출처
Applied Optics, v.60 no.4, pp.155-165
ISSN
1559-128X
출판사
Optical Society of America (OSA)
DOI
https://dx.doi.org/10.1364/AO.405991
협약과제
20HH2600, [전문연구실] 홀로그램 영상 서비스를 위한 Holo-TV 핵심 기술 개발, 박중기
초록
© 2020 Optical Society of America 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 제안 키워드
Activity map, Bit depth, Coarse Quantization, Drop drying, Dynamic speckle, Laser illumination, Non-Uniform Illumination, Non-uniform quantization, Polymer drop, Statistical processing, data compression