<p>Dynamic laser speckle imaging is a growing optical imaging technique used for exploring the dynamics of colloidal dispersions. High resolution in the spatial and temporal domain is the major attraction of this technique for analyzing complex dynamic processes of the materials. This imaging technique is both non-destructive and cost-effective, making it a valuable choice for various applications. Conventional image processing methods incorporated with the technique include Time history of speckle patterns and Co-occurrence matrices. These methods gather information from certain regions of the speckle patterns only. To avoid this limitation, frequency domain techniques are employed which isolate the areas of different activities in the complex materials. Hence, in this work, we employed Wavelet based entropy for the analysis of speckle images captured for the intermittent stages of the coagulation process of natural rubber latex. Wavelet based entropy is more effective for non-stationary processes when compared to the Fourier transform, which is applicable only to stationary processes. The results were also compared with traditional methods in the temporal domain such as Time history of speckle patterns, Co-occurrence matrices and Second-order intensity Autocorrelation function and showed agreement. Second-order intensity Autocorrelation function was employed to quantify particle size distribution of natural rubber latex during different stages of the coagulation process.</p>