Ricerc@Sapienza

Cell membranes are intrinsically heterogeneous, as the local protein and lipid distribution is critical to physiological processes. Even in template systems embedding a single protein type, like purple membranes, there can be a different local response to external stimuli or environmental factors, resulting in heterogeneous conformational changes. Despite the dramatic advances of microspectroscopy techniques, the identification of the conformation heterogeneity is still a challenging task.

We consider an acquisition system where a continuous image is reconstructed from a set of irregularly distributed noisy samples. Moreover, the system is affected by a random pointing jitter which makes the actual sampling positions different from the nominal ones. We develop a model for the system and derive the optimal, minimum variance unbiased (MVU) estimate. Unfortunately, the latter estimate is not practical to compute when the data size is large.

As an emerging nondestructive diagnostic and monitoring technique, terahertz time-domain spectroscopy (THz-TDS) imagery is attracting more attention. In this regard, new THz image processing algorithms based on infrared thermography (IRT) concepts are greatly needed, since most IRT imagery modalities are fast for in-line industrial inspection. However, this scenario is difficult due to some physical constraints to be reached, although this idea should be followed to avoid the loss of useful information during image processing.