Hybrid implementation of a real-time Radon-space image-processing system

Abstract

A unique hybrid optical-digital image-processing system that functions at real-time rates and performs analysis in Radon space is presented. This system functions by using the forward Radon transform (a mathematical tomographic transform of image data from two-dimensional image space to onedimensional Radon space), which is achieved by a front-end optical processor followed by a digital processing subsystem operating in Radon space. The system works by optically converting the two-dimensional image data into a series of one-dimensional projections. All further processing is performed digitally in Radon space on the one-dimensional projections. Using the system in transform space, we show that it can perform real-time detection of minimum-resolvable-temperature-difference measurement targets better than a human observer. Also, this paper discusses the potential of real-time object-moment analysis in Radon space. These object moments can be calculated in Radon space with significantly less image data and fewer digital processing operations than in image space. The optical front end is capable of performing 6.04 × 10(10) operations/s on the two-dimensional image data.