Megapixel mythology and photospace: estimating photospace for camera phones from large image sets

Abstract

It is a myth that more pixels alone result in better images. The marketing of camera phones in particular has focused on their pixel numbers. However, their performance varies considerably according to the conditions of image capture. Camera phones are often used in low-light situations where the lack of a flash and limited exposure time will produce underexposed, noisy and blurred images. Camera utilization can be quantitatively described by photospace distributions, a statistical description of the frequency of pictures taken at varying light levels and camera-subject distances. If the photospace distribution is known, the user-experienced distribution of quality can be determined either directly by direct measurement of subjective quality, or by photospace-weighting of objective attributes. The population of a photospace distribution requires examining large numbers of images taken under typical camera phone usage conditions. ImagePhi was developed as a user-friendly software tool to interactively estimate the primary photospace variables, subject illumination and subject distance, from individual images. Additionally, subjective evaluations of image quality and failure modes for low quality images can be entered into ImagePhi. ImagePhi has been applied to sets of images taken by typical users with a selection of popular camera phones varying in resolution. The estimated photospace distribution of camera phone usage has been correlated with the distributions of failure modes. The subjective and objective data show that photospace conditions have a much bigger impact on image quality of a camera phone than the pixel count of its imager. The 'megapixel myth' is thus seen to be less a myth than an ill framed conditional assertion, whose conditions are to a large extent specified by the camera's operational state in photospace.