Biospeckle analysis has been used as a tool to analyse biological activity with successful results in areas such as fruits, seeds and animal reproduction. These results use well-known image analysis methodology to treat the data with a second order statistical approach. Further development of this technology requires the use of new approaches to process the data and get more information, in order to make the methodology more robust and reliable. This paper presents the results of analysing biospeckle data using wavelet transformations, coefficient filtering and reconstruction, with a novel approach to increase the information obtained. The data used were from two distinct biological investigations, crop seeds and animal sperm, and the results showed that the wavelet transform was able to identify the effect of dilution in the sperm sample, allowing the isolation of nuisance covariates. The reliability of the methodology allows the development of a powerful tool to understand the influences on the patterns in the biospeckle data, even in complex materials like those observed in seeds.