Image Superresolution through a Network of Wireless Cameras

Abstract

This thesis outlines a multiple-camera wireless image superresolution system which uses off-the-shelf components. The system presented demonstrates the reconstruction of a high-resolution image from multiple low-resolution images acquired from different wireless camera nodes. Each camera node participating in the system consists of a dedicated camera for image acquisition as well as a Bluetooth USB communications card for wireless transmission of data. Low-resolution images are captured at these nodes and are transmitted to the central vision server, where they are processed and registered onto a common projective plane. The registration process is arrived at through the RANdom SAmple Consensus (RANSAC) algorithm. Once the set of low-resolution images has been registered, a single high-resolution image is reconstructed. The super-resolution process used to obtain the high-resolution output is the Projection Onto Convex Sets (POCS) technique. Reconstruction results are presented.