Retrieving controlled motion parameters using two speckle pattern analysis techniques: spatiotemporal correlation and the temporal history speckle pattern

Abstract

This paper presents simulation of speckle activity through controlling a moving plate. We present two procedures to extract the initial movement frequency and amplitude, either through correlation calculus or through processing the temporal history of the speckle pattern. We compare and discuss these two methods in terms of efficiency and the ability to retrieve motion parameters. The correlation technique seems to be more suitable for monitoring biospeckle activity as it provides more reliable parameter estimation than the temporal history of the speckle pattern. The evolution of temporal history of the speckle pattern parameters and their response sensibility with amplitude and frequency variations have been studied and quantified. Briers contrast appears to depend only on movement amplitude, whereas inertia moment varies with amplitude and frequency.

Detection of Golden apples’ climacteric peak by laser biospeckle measurements

“…m and n represent the pixel number (m 1; …; 768, and n 1; …; 541) and Δr is the pixel size [8,16]. It 0 ; x 0 ; y 0 represents the mean intensity of the first acquired speckle image at t 0 s and It; x; y is the m; n pixel intensity of the series acquired speckle image at t s. By summing P m;n Ct; mΔr; nΔr and varying the time offset, one can obtain the temporal correlation coefficient Ct.…”

Assessing White Wine Viscosity Variation Using Polarized Laser Speckle: A Promising Alternative to Wine Sensory Analysis

“…For the temporal approach, speckle images were analyzed by computing the speckle intensity correlation on one hand [ 23 ], and extracting the temporal history of the speckle pattern (THSP) matrix on the other [ 24 , 25 ].…”

“…For each sample, we acquired a temporal series of speckle images with a frame rate of 2130 fps. We computed the speckle intensity correlation with the mean of a cross correlation analysis between the first speckle image intensity and the k-th speckle image intensity using where is the time, , , , and are the pixel positions in the image, and is the pixel size [ 23 ]. An example of the temporal correlation curve is plotted in Figure 2 a as a function of time, giving an idea of the analyzed sample activity evolution.…”

“… is useful for estimating a sample’s total activity. When the activity of a sample decreases, its variations become slower, and thus decreases [ 23 , 28 , 29 ].…”

“…In our work, we evaluate and compare various approaches of the polarized speckle field. Speckle patterns are analyzed by evaluating the spatial contrast [ 20 , 22 ], the temporal correlation coefficient [ 23 ], and the temporal history of the speckle pattern (THSP) [ 23 , 24 , 25 ].…”