The Implementation of Compressive Sensing Architecture for Endoscopy Image Acquisition and Reconstruction over Body-to-body Networks

In recent years, Compressive Sensing (CS) has a lot of outstanding applications in areas of signal processing. CS can be used to capture endoscopy images with data acquisition and reconstruction principles. This paper explains the implementation of compressive sensing in endoscopy system, aiming to facilitate efficient examination of the ears, nose, and throat (ENT) and enabling the delivery of patient disease information quickly and independently. To conduct comprehensive experiments, we use the strict testing methods involving image acquisition, Orthogonal Matching Pursuit (OMP) reconstruction, scheduling mechanism in body-to-body networks (BBN), and website development using throat image samples. Based on the results of the compressive sensing test in endoscopy images, it can be concluded that the prototype system is considered operational and suitable for future use.