Towards infrared image understanding
An extensive literature survey has revealed that the majority of previous work in infrared image processing has ignored the processes leading to the formation of infrared images. Processing has normally either been restricted to simple lowlevel image enhancement convolutions or has consisted of algorithms copied from computer vision without regard for the inherent differences between infrared and visible images. In this thesis, we address the problem of infrared image formation and derive an irradiance equation for simple infrared scenes. We consider the complications caused by mutual illumination of one or more bodies and indicate how the infrared irradiance equation can also be specified for more complex scenes. The infrared irradiance equation we derive is solved in closed form for some simple geometries for both Lambertian and non-Lambertian surfaces. An infrared imager has been built and is described. Images taken with the imager of a variety of scene geometries show that the experimental results compare favourably with the theoretically derived equations, indicating the validity of the theoretical analysis. We describe how a knowledge of the formation of infrared images can be used to predict the image irradiance pattern of a particular object. We also show how, with a knowledge of the radiance properties and surface geometry of the object, it is possible to detect instances of that object in a scene. Examples are given of successful object detection based on an understanding of the image irradiance. We present a brief history of infrared imagers and a description of the principles on which modern infrared imagers are based. In addition to the survey of the literature published on infrared image processing, a brief summary of some techniques from the computer vision literature and their suitability to infrared image processing is given. A selection of vision techniques are applied to both infrared and visible images to verify conclusions reached in the thesis.