Defocus Deblurring Research Articles

基于编码孔径的折反射全向成像去散焦模糊技术

基于编码孔径的折反射全向成像去散焦模糊技术

Perceptually Optimized Coded Apertures for Defocus Deblurring

AbstractThe field of computational photography, and in particular the design and implementation of coded apertures, has yielded impressive results in the last years. In this paper we introduce perceptually optimized coded apertures for defocused deblurring. We obtain near‐optimal apertures by means of optimization, with a novel evaluation function that includes two existing image quality perceptual metrics. These metrics favour results where errors in the final deblurred images will not be perceived by a human observer. Our work improves the results obtained with a similar approach that only takes into account the L2 metric in the evaluation function.

Programmable Aperture Camera Using LCoS

Since 1960s, aperture patterns have been studied extensively and a variety of coded apertures have been proposed for various applications, including extended depth of field, defocus deblurring, depth from defocus, light field acquisition, etc. Researches have shown that optimal aperture patterns can be quite different due to different applications, imaging conditions, or scene contents. In addition, many coded aperture techniques require aperture patterns to be temporally changed during capturing. As a result, it is often necessary to have a programmable aperture camera whose aperture pattern can be dynamically changed as needed in order to capture more useful information. In this paper, we propose a programmable aperture camera using a Liquid Crystal on Silicon (LCoS) device. This design affords a high brightness contrast and high resolution aperture with a relatively low light loss, and enables one change the pattern at a reasonably high frame rate. We build a prototype camera and evaluate its features and drawbacks comprehensively by experiments. We also demonstrate three coded aperture applications in defocus deblurring, depth from defocus and light field acquisition.

去散焦模糊的折反射全向成像系统设计

去散焦模糊的折反射全向成像系统设计

Coded Aperture Pairs for Depth from Defocus and Defocus Deblurring

The classical approach to depth from defocus (DFD) uses lenses with circular apertures for image capturing. We show in this paper that the use of a circular aperture severely restricts the accuracy of DFD. We derive a criterion for evaluating a pair of apertures with respect to the precision of depth recovery. This criterion is optimized using a genetic algorithm and gradient descent search to arrive at a pair of high resolution apertures. These two coded apertures are found to complement each other in the scene frequencies they preserve. This property enables them to not only recover depth with greater fidelity but also obtain a high quality all-focused image from the two captured images. Extensive simulations as well as experiments on a variety of real scenes demonstrate the benefits of using the coded apertures over conventional circular apertures.

Perceptually-Motivated Coded Apertures

Computational perception techniques are gaining increasing importance in all different steps of the imaging pipeline, from data capture to final display. The goal of these techniques is usually the same: to minimize visible errors in the final image. We present a method to compute coded apertures for defocus deblurring that takes into account human perception to obtain the optimal aperture pattern. We pose the problem of finding the optimal aperture as an optimization, and -to our knowledge- propose the first algorithm that makes use of perceptual quality metrics in its objective function. We explore the performance of different quality metrics for the design of such coded apertures, including the well-established SSIM, the state-of-the-art HDR-VDP-2, which features a comprehensive model of the HVS, as well as the L2 norm, previously used in related works.Our results outperform both conventional circular apertures and a previously published aperture pattern specifically designed for defocus deblurring [1], both in simulated and real scenarios (see Figures 1 and 2). The best apertures are obtained when a combination of the three metrics is used in the objective function. This work has been recently accepted for publication at the Computer Graphics Forum [2].