Compressive light field photography using overcomplete dictionaries and optimized projections Citation
نویسندگان
چکیده
Light field photography has gained a significant research interest in the last two decades; today, commercial light field cameras are widely available. Nevertheless, most existing acquisition approaches either multiplex a low-resolution light field into a single 2D sensor image or require multiple photographs to be taken for acquiring a high-resolution light field. We propose a compressive light field camera architecture that allows for higher-resolution light fields to be recovered than previously possible from a single image. The proposed architecture comprises three key components: light field atoms as a sparse representation of natural light fields, an optical design that allows for capturing optimized 2D light field projections, and robust sparse reconstruction methods to recover a 4D light field from a single coded 2D projection. In addition, we demonstrate a variety of other applications for light field atoms and sparse coding techniques, including 4D light field compression and denoising.
منابع مشابه
Compressive Light Field Photographysing Overcomplete Dictionaries and Optimized Projections
Light field photography has gained a significant research interest in the last two decades; today, commercial light field cameras are widely available. Nevertheless, most existing acquisition approaches either multiplex a low-resolution light field into a single 2D sensor image or require multiple photographs to be taken for acquiring a high-resolution light field. We propose a compressive ligh...
متن کاملResolution Preserving Light Field Photography Using Overcomplete Dictionaries And Incoherent Projections
1 We present a computational framework and mask-based optical de2 sign for resolution-preserving light field reconstructions from a sin3 gle modulated sensor image. Compressive computational recon4 struction techniques are used in combination with learned overcom5 plete dictionaries that capture the essential building blocks of natu6 ral light fields. The mask patterns in the camera create inco...
متن کاملCompressive Sensing for Inverse Scattering
Compressive sensing is a new field in signal processing and applied mathematics. It allows one to simultaneously sample and compress signals which are known to have a sparse representation in a known basis or dictionary along with the subsequent recovery by linear programming (requiring polynomial (P) time) of the original signals with low or no error [1–3]. Compressive measurements or samples ...
متن کاملGreedy Signal Space Methods for incoherence and beyond
ABSTRACT. Compressive sampling (CoSa) has providedmany methods for signal recovery of signals compressible with respect to an orthonormal basis. However, modern applications have sparked the emergence of approaches for signals not sparse in an orthonormal basis but in some arbitrary, perhaps highly overcomplete, dictionary. Recently, several “signal-space” greedymethods have been proposed to ad...
متن کاملOvercomplete Dictionaries for Scene Classification in Coded-Aperture Spectral Imaging
I. INTRODUCTION Traditional spectral imaging sensors entail the acquisition of high-dimensional data that is used for the discrimination of objects and features in a scene. Recently, a novel architecture known as coded aperture snapshot spectral imaging (CASSI) system has been proposed for the acquisition of compressive spectral image data of a scene with just a few coded focal plane array (FPA...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2013