Browsing by Author "Levchenko M."

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    Dynamic speckle imaging with SVD compression
    (2022-01-01) Stoykova E.; Levchenko M.; Ivanov B.; Madjarova V.; Nazarova D.; Nedelchev L.; Machikhin A.; Park J.
    Dynamic speckle imaging (DSI) of areas with different speed of processes ongoing in industrial or biological objects relies on statistical processing of a large number of images of the speckle patterns formed on the objects surface under laser illumination. The DSI visualizes the speed spatial distribution as an activity map. We propose compression of the raw DSI data by applying singular value decomposition (SVD). A specific feature of speckle images for DSI is lack of a structure with areas of close intensity values. The gain from the direct SVD application may be modest in cases when a great number of non-zero singular values is needed to build an activity map comparable in quality to the ground truth map from bitmap images. For higher compression, we propose SVD to be applied to the 2D arrays containing the differences between the successive images. The SVD compression has been verified by using synthetic and experimental data.
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    Intensity-based dynamic speckle method for analysis of variable-rate dynamic events
    (2023-01-01) Stoykova E.; Nedelchev L.; Blagoeva B.; Ivanov B.; Levchenko M.; Berberova-Buhova N.; Nazarova D.
    We study efficiency of intensity-based dynamic speckle method for characterization of dynamic events which occur at variable rate in time within the temporal averaging interval. We checked the ability of the method to describe the speed of evolution by i) numerical simulation at variable speed, ii) processing of speckle patterns obtained from phase distributions fed to a SLM at controllable change of the temporal correlation radius of speckle intensity fluctuations and iii) conducting experiments with a polymer solution drying by using a hot-stage. The numerical and SLM simulation experiments allowed for modification of the used estimates in order to obtain relevant information.
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    Intensity-based dynamic speckle method using JPEG and JPEG2000 compression
    (2022-02-10) Stoykova E.; Blagoeva B.; Berberova-Buhova N.; Levchenko M.; Nazarova D.; Nedelchev L.; Park J.
    Statistical processing of speckle data enables observation of the speed of processes. In intensity-based pointwise dynamic speckle analysis, a map related to speed’s spatial distribution is extracted from a sequence of speckle patterns formed on an object under coherent light. Monitoring of time evolution of a process needs storage, transfer, and processing of a large number of images. We have proposed lossy compression of these images using JPEG and JPEG2000 formats. We have compared the maps computed from noncompressed and decompressed synthetic and experimental images, and we have proven that both compression formats can be applied in the dynamic speckle analysis.
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    Noise analysis in outdoor dynamic speckle measurement
    (2023-04-01) Levchenko M.; Stoykova E.; Ivanov B.; Nedelchev L.; Nazarova D.; Choi K.; Park J.
    The dynamic speckle method (DSM) is an effective tool for the estimation of speed of processes. The speed distribution is encoded in a map built by statistical pointwise processing of time-correlated speckle patterns. For industrial inspection, the outdoor noisy measurement is required. The paper analyzes the efficiency of the DSM in the presence of environmental noise as phase fluctuations due to the lack of vibration isolation and shot noise due to ambient light. The usage of normalized estimates for the case of non-uniform laser illumination is studied. The feasibility of the outdoor measurement has been proven by numerical simulations of noisy image capture and real experiments with test objects. Good agreement has been demonstrated in both the simulation and experiment between the ground truth map and the maps extracted from noisy data.
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    Normalization in dynamic speckle analysis for non-destructive monitoring of speed of processes
    (2021-12-17) Stoykova E.; Nazarova D.; Nedelchev L.; Levchenko M.; Berberova-Buhova N.; Ivanov B.
    The paper is dedicated to analysis of normalized intensity-based pointwise algorithms for processing dynamic speckle images with spatially varying speckle statistics in non-destructive visualization of regions of faster or slower changes across an object. Both existing and newly proposed algorithms are analyzed. Extraction of speed of changes is done by acquiring correlated in time speckle images formed on the object surface under laser illumination. The studied algorithms have been applied to simulated low and high contrast speckle data. Their performance has been compared to processing of binary patterns as another approach for dealing with varying speckle statistics in the acquired images. The efficiency of the algorithms have been checked on the experimental data, including data in a compressed format. We have proven that the algorithms with normalization at successive instants by a sum of two intensities or a single intensity outperform as a whole the algorithms which apply the time-averaged estimates of the mean value and the variance of speckle intensity.