Correcting for optical aberrations using multilayer displays

Optical aberrations of the human eye are currently corrected using eyeglasses, contact lenses, or surgery. We describe a fourth option: modifying the composition of displayed content such that the perceived image appears in focus, after passing through an eye with known optical defects. Prior approaches synthesize pre-filtered images by deconvolving the content by the point spread function of the aberrated eye. Such methods have not led to practical applications, due to severely reduced contrast and ringing artifacts. We address these limitations by introducing multilayer pre-filtering, implemented using stacks of semi-transparent, light-emitting layers. By optimizing the layer positions and the partition of spatial frequencies between layers, contrast is improved and ringing artifacts are eliminated. We assess design constraints for multilayer displays; autostereoscopic light field displays are identified as a preferred, thin form factor architecture, allowing synthetic layers to be displaced in response to viewer movement and refractive errors. We assess the benefits of multilayer pre-filtering versus prior light field pre-distortion methods, showing pre-filtering works within the constraints of current display resolutions. We conclude by analyzing benefits and limitations using a prototype multilayer LCD.National Science Foundation (U.S.) (Grant IIS-1116452)Alfred P. Sloan Foundation (Research Fellowship)United States. Defense Advanced Research Projects Agency (Young Faculty Award)Vodafone (Firm) (Wireless Innovation Award

Eyeglasses-free display: towards correcting visual aberrations with computational light field displays

Millions of people worldwide need glasses or contact lenses to see or read properly. We introduce a computational display technology that predistorts the presented content for an observer, so that the target image is perceived without the need for eyewear. By designing optics in concert with prefiltering algorithms, the proposed display architecture achieves significantly higher resolution and contrast than prior approaches to vision-correcting image display. We demonstrate that inexpensive light field displays driven by efficient implementations of 4D prefiltering algorithms can produce the desired vision-corrected imagery, even for higher-order aberrations that are difficult to be corrected with glasses. The proposed computational display architecture is evaluated in simulation and with a low-cost prototype device.National Science Foundation (U.S.) (grant number IIS-1219241)National Science Foundation (U.S.) (grant number IIS-1116718)Natural Sciences and Engineering Research Council of Canada (NSERC Postdoctoral Fellowship

Augmented reality fonts with enhanced out-of-focus text legibility

In augmented reality, information is often distributed between real and virtual contexts, and often appears at different distances from the viewer. This raises the issues of (1) context switching, when attention is switched between real and virtual contexts, (2) focal distance switching, when the eye accommodates to see information in sharp focus at a new distance, and (3) transient focal blur, when information is seen out of focus, during the time interval of focal distance switching. This dissertation research has quantified the impact of context switching, focal distance switching, and transient focal blur on human performance and eye fatigue in both monocular and binocular viewing conditions. Further, this research has developed a novel font that when seen out-of-focus looks sharper than standard fonts. This SharpView font promises to mitigate the effect of transient focal blur. Developing this font has required (1) mathematically modeling out-of-focus blur with Zernike polynomials, which model focal deficiencies of human vision, (2) developing a focus correction algorithm based on total variation optimization, which corrects out-of-focus blur, and (3) developing a novel algorithm for measuring font sharpness. Finally, this research has validated these fonts through simulation and optical camera-based measurement. This validation has shown that, when seen out of focus, SharpView fonts are as much as 40 to 50% sharper than standard fonts. This promises to improve font legibility in many applications of augmented reality