Image Matching and Registration

Abstract

When we compare two images, we are faced with the following basic question: when are two images the same or similar, and how can this similarity be measured? Of course one could trivially define two images I1, I2 as being identical when all pixel values are the same (i.e., the difference I1 – I2 is zero). Although this kind of definition may be useful in specific applications, such as for detecting changes in successive images under constant lighting and camera conditions, simple pixel differencing is usually too inflexible to be of much practical use. Noise, quantization errors, small changes in lighting, and minute shifts or rotations can all create large numerical pixel differences for pairs of images that would still be perceived as perfectly identical by a human viewer.