We propose a square aperture as a simple and practical alternative to existing coded aperture. A spatial derivative converts sensor measurements taken with a square aperture mask into measurements taken with a pinhole or slit aperture mask. Thus square aperture shares the properties of both large and small apertures, yielding excellent light efficiency while an artificial small aperture results in an infinite depth of field. We developed a prototype lens to confirm the feasibility of our blur size estimation and image deblurring approach.
Smartphone cameras have progressed a lot during recent years and even caught up with entry-level DSLR cameras in many standard situations. One domain where the difference remained obvious was portrait photography. Now smartphone manufacturers equip their flagship models with special modes where they computationally simulate shallow depth of field. We propose a method to quantitatively evaluate the quality of such computational bokeh in a reproducible way, focusing on both the quality of the bokeh (depth of field, shape), as well as on artifacts brought by the challenge to accurately differentiate the face of a subject from the background, especially on complex transitions such as curly hairs. Depth of field simulation is a complex topic and standard metrics for out-of-focus blur do not currently exist. The proposed method is based on perceptual, systematic analysis of pictures shot in our lab. We show that the depth of field of the best mobile devices is as shallow as that of DSLRs, but also reveal processing artifacts that are inexistent on DSLRs. Our primary goal is to help customers comparing smartphone cameras among each other and to DSLRs. We also hope that our method will guide smartphone makers in their developments and will thereby contribute to advancing mobile portrait photography.
The depth of field (DOF) of an auto-stereoscopic display refers to the depth range in 3D space in which objects can be depicted with small amount of blur. It provides a measurable index on the display's performance in reproducing light fields of 3D scenes. Previous studies have analyzed the maximum spatial frequencies of aliasing-free images depicted on planes parallel to the display's surface. For multilayer displays, several formulae representing the upper bounds on the maximum frequencies have been given. However, these formulae provide little information on how much blur would be present in the reproduced fields, since contributions of low frequency signals are simply neglected. Such signals are frequently damaged on multilayer displays especially when the angular range of viewing angles becomes wide. To address these drawbacks, we present a novel framework for the DOF analysis of multilayer displays. The analysis begins with a close look at the synthesis of layer images, which can be considered as solving a linear least squares problem with nonnegativity constraints. This numerical procedure is then reinterpreted in the context of multilayer displays, where part of the connections between "depth" and "blur" are observed. Finally, experimental results supporting these observations are presented.