58 research outputs found
Adaptive Temporal Compressive Sensing for Video
This paper introduces the concept of adaptive temporal compressive sensing
(CS) for video. We propose a CS algorithm to adapt the compression ratio based
on the scene's temporal complexity, computed from the compressed data, without
compromising the quality of the reconstructed video. The temporal adaptivity is
manifested by manipulating the integration time of the camera, opening the
possibility to real-time implementation. The proposed algorithm is a
generalized temporal CS approach that can be incorporated with a diverse set of
existing hardware systems.Comment: IEEE Interonal International Conference on Image Processing
(ICIP),201
Efficient Space-Time Sampling with Pixel-wise Coded Exposure for High Speed Imaging
Cameras face a fundamental tradeoff between spatial and temporal resolution. Digital still cameras can capture images with high spatial resolution, but most high-speed video cameras have relatively low spatial resolution. It is hard to overcome this tradeoff without incurring a significant increase in hardware costs. In this paper, we propose techniques for sampling, representing and reconstructing the space-time volume in order to overcome this tradeoff. Our approach has two important distinctions compared to previous works: (1) we achieve sparse representation of videos by learning an over-complete dictionary on video patches, and (2) we adhere to practical hardware constraints on sampling schemes imposed by architectures of current image sensors, which means that our sampling function can be implemented on CMOS image sensors with modified control units in the future. We evaluate components of our approach - sampling function and sparse representation by comparing them to several existing approaches. We also implement a prototype imaging system with pixel-wise coded exposure control using a Liquid Crystal on Silicon (LCoS) device. System characteristics such as field of view, Modulation Transfer Function (MTF) are evaluated for our imaging system. Both simulations and experiments on a wide range of scenes show that our method can effectively reconstruct a video from a single coded image while maintaining high spatial resolution
Coded aperture compressive temporal imaging.
We use mechanical translation of a coded aperture for code division multiple access compression of video. We discuss the compressed video's temporal resolution and present experimental results for reconstructions of > 10 frames of temporal data per coded snapshot
Compressive Holographic Video
Compressed sensing has been discussed separately in spatial and temporal
domains. Compressive holography has been introduced as a method that allows 3D
tomographic reconstruction at different depths from a single 2D image. Coded
exposure is a temporal compressed sensing method for high speed video
acquisition. In this work, we combine compressive holography and coded exposure
techniques and extend the discussion to 4D reconstruction in space and time
from one coded captured image. In our prototype, digital in-line holography was
used for imaging macroscopic, fast moving objects. The pixel-wise temporal
modulation was implemented by a digital micromirror device. In this paper we
demonstrate temporal super resolution with multiple depths recovery
from a single image. Two examples are presented for the purpose of recording
subtle vibrations and tracking small particles within 5 ms.Comment: 12 pages, 6 figure
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