An Approach To Acquiring High Resolution Images Using Multiple Cameras

Abstract

In recent years, researchers in the advanced television system area have concentrated on high definition television(HDTV). Although HDTV has has twice the spatial resolution as compared to current broadcasting television, in comparison to 35-mm film which is considered to be a typical quality criterion in non-electronic visual media, HDTV quality is still insufficient. When the FTTH (Fiber To The Home) based telecommunication is realized in the future then it will provide us with large transmission capacity and there is still an open way to much higher difinition image communication with at least '2000x2000 pixel resolution which are expected to integrate all visual information including non-electronic materials such as 35-mm films for printing, motion pictures, etc,. Image acquisition method is one of the principal problems for handling very high resolution images. Although a CCD camera with two million pixels has already been developed for HDTV, it is still necessary to increase the resolution further for dealing with very high resolution images. Reducing the size of pixels is one way to increase resolution. However, the smaller the pixel size is, the amount of light available for each pixel is less and the picture quality is degraded since the existence of shot-noise (variation of input) is inevitable in principle. There needs to be a limitation in the pixel size reduction in order to keep shot noise invisible on a monitor. Current CCD technology has almost reached this bound. Thus, new schemes are required to increase the resolution even further. One promising approach to further improve resolution is to incorporate signal processing techniques into the imaging process. iFrom the signal processing point of view, we propose a new imaging scheme to acquire high resolution images by processing multiple pictures. Proposed method contains two different mechanisms to further increase resolution. In one mechanism, sampling sequences of two camera are integrated together after their relative discrepancies are estimated, and higher frequencies are reconstructed from this integrated double density sampling points. The other mechanism improves signal-to-noise-ratio by averaging the higher resolution images reconstructed by coupling different two images among multiple cameras. SJN improvement enables us to furt,her reduce pixel size in advance because resolution and S/N have trade-off relationship. Our preliminary experiment have clearly shown the improvements in the high frequencies and details.