In this work the measured variable, such as temperature, is a random variable showing fluctuations. The loss of information caused by diffusion waves in nondestructive testing can be described by stochastic processes. In non-destructive imaging, the information about the spatial pattern of a samples interior has to be transferred to the sample surface by certainwaves, e.g., thermalwaves. At the sample surface these waves can be detected and the interior structure is reconstructed from the measured signals. The amount of information about the interior of the sample, which can be gained from the detected waves on the sample surface, is essentially influenced by the propagation from its excitation to the surface. Diffusion causes entropy production and information loss for the propagating waves. Mandelis has developed a unifying framework for treating diverse diffusion-related periodic phenomena under the global mathematical label of diffusion-wave fields, such as thermal waves. Thermography uses the time-dependent diffusion of heat (either pulsed or modulated periodically) which goes along with entropy production and a loss of information. Several attempts have been made to compensate for this diffusive effect to get a higher resolution for the reconstructed images of the samples interior. In this work it is shown that fluctuations limit this compensation. Therefore, the spatial resolution for non-destructive imaging at a certain depth is also limited by theory.