The laser speckle technique provides a non-invasive remote sensing method for monitoring biological dynamics. In this study, we focus on assessing microbial growth through systematic comparison of correlation-based speckle image analysis methods. We compare conventional techniques, NCC, ZNCC, the Lewis method, and Phase correlation, with two newly proposed variants: frequency-domain correlation of normalized images and ZNCC with limited shifts around the peak. We analyze these methods in terms of precision and computational efficiency. Our results demonstrate that the proposed techniques offer optimal trade-offs for tracking subtle microbial activity, particularly in early-stage growth. This paper aims not only to identify the most effective tools for laser speckle analysis, but also to justify the use of laser speckle imaging for microbial activity assessment.