Shannon information capacity, which can be expressed as bits per pixel or megabits per image, is an excellent figure of merit for predicting camera performance for a variety of machine vision applications, including medical and automotive imaging systems.
Its strength is that is combines the effects of sharpness (MTF) and noise, but it has not been widely adopted because it has been difficult to measure and has never been standardized.
We have developed a method for conveniently measuring information capacity from images of the familiar sinusoidal Siemens Star chart. The key is that noise is measured in the presence of the image signal, rather than in a separate location where image processing may be different—a commonplace occurrence with bilateral filters. The method also enables measurement of SNRI, which is a key performance metric for object detection.
Information capacity is strongly affected by sensor noise, lens quality, ISO speed (Exposure Index), and the demosaicing algorithm, which affects aliasing. Information capacity of in-camera JPEG images differs from corresponding TIFF images from raw files because of different demosaicing algorithms and nonuniform sharpening and noise reduction.
Author: Norman Koren, founder and CTO
Presented at Electronic Imaging 2020