The third design is a three-dimensional compressive sensing (3DCS) camera for video acquisition. Theoretical and experimental results show that this new TVL1 achieves higher recovery accuracy than the previous TV measure TVL1L2 in decoding images from compressive measurements. In addition, we propose a new L1-norm based total-variation measure TVL1, which enforces the sparsity and the directional continuity in the partial gradient domain. First, this hybrid compressive sensing camera further reduces the sampling rate of compressive sensing by combining the traditional MTM random sampling with MTO low-resolution sampling. The second design is a hybrid compressive sensing camera for image acquisition. The physical implementation of the multiplexed imaging system is presented to show (1) the effectiveness of providing access to the aperture and (2) the advantages of aperture manipulation in computational imaging applications.
Specifically, a rear-attached relay system (lens) is mounted behind the imaging lens to reposition the aperture plane outside the imaging lens. In this system, a novel approach is proposed to provide an external aperture that enables dynamic control of its transmission, position and orientation.
Multiplexed imaging often involves manipulating the incoming light beam on the aperture, which is located inside the lens housing and thus is challenging to access or modulate. The first design is a multiplexed imaging system that accesses and manipulates the lens aperture for many computational imaging applications. On the other hand, compressive sensing, also called compressive sampling, aims at acquiring a signal/image at a lower sampling rate (below the Nyquist rate) by exploiting (1) the MTM random sampling and (2) the prior knowledge that a signal/image is sparse or correlated in some domain. On one hand, multiplexed sensing attempts to acquire multi-modality information from the outside scene by multi-channel sensing and fuses a more informative image. Multipled sensing and compressive sensing attempt to improve conventional OTO cameras by exploring other object-to-image mapping models, such as one-to-multiple (OTM) divergent mapping, multiple-to-one (MTO) convergent mapping and multiple-to-multiple (MTM) random mapping, and respectively achieve two different advanced imaging functions.
Conventional cameras (e.g., pin-hole and lens cameras) follow the one-object-point-to-one-image-point or one-to-one (OTO) mapping model. This dissertation works on advanced imaging systems using multiplexed sensing and compressive sensing (CS).
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