Due to the fast evolving technologies and the increasing importance of Social Media, the camera is one of the most important components of today's mobile phones. Nowadays, smartphones are taking over a big share of the compact camera market. A simple reason for this might be revealed by the famous quote: "The best camera is the one that's with you". But with the vast choice of devices and great promises of manufacturers, there is a demand to characterize image quality and performance in very simple terms in order to provide information that helps choosing the best-suited device. The current existing evaluation systems are either not entirely objective or are under development and haven't reached a useful level yet. Therefore the industry itself has gotten together and created a new objective quality evaluation system named Valued Camera eXperience (VCX). It is designed to reflect the user experience regarding the image quality and the performance of a camera in a mobile device. Members of the initiative so fare are: Apple, Huawei, Image Engineering, LG, Mediatec, Nomicam, Oppo, TCL, Vivo, and Vodafone.
Right now there are at least three publicly known ranking systems for cell phones (CPIQ [IEEE P1858, in preparation, DxOmark, VCX) that try to tell us which camera phone provides the best image quality. Now that IEEE is about to publish the P1858 standard with currently only 6 Image quality parameters the question arises how many parameters are needed to characterize a camera in a current cell phone and how important is each factor for the perceived quality. For testing the importance of a factor the IEEE cellphone image quality group (CPIQ) has created psychophysical studies for all 6 image quality factors that are described in the first version of IEEE P1858. That way a connection between the physical measurement of the image quality aspect and the perceived quality can be made.
Increased demand for high-resolution projection displays makes the projector industry search for ways of enhancing the resolution above the native resolution of the projector's image panel. Resolution enhancement through superimposition is one method of enhancing the resolution that has gained popularity in the industry the last couple of years. This method consists of shifting every other projected frame spatially with sub-pixel precision, and by doing so creating a new pixel grid on the projected surface with smaller effective pixel pitch. There is still an open question of how well this technique performs in comparison to the native resolution, and how high the effective resolution gain really is. To determine which application the superimposition method is best suited for, it is also interesting to look at how this method performs over different kinds of image and video content. To help investigate these questions we have developed a simulator that simulates different superimposition methods over several classes of image content. The superimposed images are then evaluated by several image quality metrics with the goal of finding out which quality metrics are most applicable to the superimpositioning case. We found that the MSSSIM metric is the most suitable to evaluate superimposed images. VIF also performs quite well, but MSSSIM performs slightly better. However, none of these metrics identifies all the artefacts introduced by the superimpositioning. More research is needed to develop an ideal metric.