US 12,333,734 B2
System and method for imaging of localized and heterogeneous dynamics using laser speckle
Parama Pal, Bangalore (IN); and Earu Banoth, Bangalore (IN)
Assigned to TATA CONSULTANCY SERVICES LIMITED, Mumbai (IN)
Filed by Tata Consultancy Services Limited, Mumbai (IN)
Filed on Mar. 7, 2022, as Appl. No. 17/687,889.
Claims priority of application No. 202121009917 (IN), filed on Mar. 9, 2021.
Prior Publication US 2022/0343510 A1, Oct. 27, 2022
Int. Cl. G06T 7/174 (2017.01); G06T 3/4007 (2024.01)
CPC G06T 7/174 (2017.01) [G06T 3/4007 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/10056 (2013.01)] 9 Claims
OG exemplary drawing
 
1. A processor-implemented method, comprising:
recording, via one or more hardware processors, an image stack consisting of N speckle images, wherein size of each of the speckle image is equal to K*L which is recorded sequentially over a period of time, and wherein K indicates the number of rows and L indicates the number of columns of each of the speckle image;
dividing, via the one or more hardware processors, the image stack into a spatial window of size Kp*Lp and a temporal window of Np around patches of each of the speckle image, wherein the spatial window comprises speckle intensity data, and wherein p denotes a subset of K and L comprised in each of the speckle image;
converting, via the one or more hardware processors, the speckle intensity data comprised in the spatial window into a column vector Vp of length Kp*Lp*1 for each of the speckle image to obtain a plurality of column vectors Vp;
constructing, via the one or more hardware processors, a diagonal matrix Σp based on Kp, Np and Lp;
extracting, via the one or more hardware processors, a singular value σi from the diagonal matrix Σp, wherein a total number of a plurality of singular values σi is represented by min (KpLpVp);
defining, via the one or more hardware processors, a speckle intensity correlation metric (CM) using the plurality of singular values σ1:

OG Complex Work Unit Math
defining, via the one or more hardware processors, a speckle activity (SA) using the defined speckle intensity correlation metric (CM), wherein a plurality of regions of high activity is represented by high speckle activity (SA) values and a plurality of regions of low activity is represented by low speckle activity (SA) values, wherein the speckle activity (SA) is expressed using the equation:

OG Complex Work Unit Math
generating, via the one or more hardware processors, a speckle contrast image by graphically plotting the speckle activity (SA) values to generate an activity map and performing an interpolation across the activity map to obtain an interpolated activity map.