High frame rate video (HFV) is an important investigational tool in sciences, engineering and military. In ultrahigh speed imaging, the obtainable temporal, spatial and spectral resolutions are limited by the sustainable throughput of in-camera mass memory, the lower bound of exposure time, and illumination conditions. In order to break these bottlenecks, we propose a new coded video acquisition framework that employs K>1 cameras, each of which makes random measurements of the video signal in both temporal and spatial domains. For each of the K cameras, this multi-camera strategy greatly relaxes the stringent requirements in memory speed, shutter speed, and illumination strength. The recovery of HFV from these random measurements is posed and solved as a large scale l1 minimization problem by exploiting joint temporal and spatial sparsities of the 3D signal. Three coded video acquisition techniques of varied trade o s between performance and hardware complexity are developed: frame-wise coded acquisition, pixel-wise coded acquisition, and column-row-wise coded acquisition. The performances of these techniques are analyzed in relation to the sparsity of the underlying video signal.
To make ultra high speed cameras of coded exposure more practical and a fordable, we develop a coded exposure video/image acquisition system by an innovative assembling of multiple rolling shutter cameras. Each of the constituent rolling shutter cameras adopts a random pixel read-out mechanism by simply changing the read out order of pixel rows from sequential to random.
Simulations of these new image/video coded acquisition techniques are carried out and experimental results are reported. / Dissertation / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/16887 |
| Date | 10 April 2015 |
| Creators | Pournaghi, Reza |
| Contributors | Wu, Xiaolin, Electrical and Computer Engineering |
| Source Sets | McMaster University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
Page generated in 0.0022 seconds