TY - GEN
T1 - Video compressive sensing with on-chip programmable subsampling
AU - Spinoulas, Leonidas
AU - He, Kuan
AU - Cossairt, Oliver Strides
AU - Katsaggelos, Aggelos K
PY - 2015/10/19
Y1 - 2015/10/19
N2 - The maximum achievable frame-rate for a video camera is limited by the sensor's pixel readout rate. The same sensor may achieve either a slow frame-rate at full resolution (e.g., 60 fps at 4 Mpixel resolution) or a fast frame-rate at low resolution (e.g., 240 fps at 1 Mpixel resolution). Higher frame-rates are achieved using pixel readout modes (e.g., subsampling or binning) that sacrifice spatial for temporal resolution within a fixed bandwidth. A number of compressive video cameras have been introduced to overcome this fixed bandwidth constraint and achieve high frame-rates without sacrificing spatial resolution. These methods use electro-optic components (e.g., LCoS, DLPs, piezo actuators) to introduce high speed spatio-temporal multiplexing in captured images. Full resolution, high speed video is then restored by solving an undetermined system of equations using a sparse regularization framework. In this work, we introduce the first all-digital temporal compressive video camera that uses custom subsampling modes to achieve spatio-temporal multiplexing. Unlike previous compressive video cameras, ours requires no additional optical components, enabling it to be implemented in a compact package such as a mobile camera module. We demonstrate results using a TrueSense development kit with a 12 Mpixel sensor and programmable FPGA read out circuitry.
AB - The maximum achievable frame-rate for a video camera is limited by the sensor's pixel readout rate. The same sensor may achieve either a slow frame-rate at full resolution (e.g., 60 fps at 4 Mpixel resolution) or a fast frame-rate at low resolution (e.g., 240 fps at 1 Mpixel resolution). Higher frame-rates are achieved using pixel readout modes (e.g., subsampling or binning) that sacrifice spatial for temporal resolution within a fixed bandwidth. A number of compressive video cameras have been introduced to overcome this fixed bandwidth constraint and achieve high frame-rates without sacrificing spatial resolution. These methods use electro-optic components (e.g., LCoS, DLPs, piezo actuators) to introduce high speed spatio-temporal multiplexing in captured images. Full resolution, high speed video is then restored by solving an undetermined system of equations using a sparse regularization framework. In this work, we introduce the first all-digital temporal compressive video camera that uses custom subsampling modes to achieve spatio-temporal multiplexing. Unlike previous compressive video cameras, ours requires no additional optical components, enabling it to be implemented in a compact package such as a mobile camera module. We demonstrate results using a TrueSense development kit with a 12 Mpixel sensor and programmable FPGA read out circuitry.
KW - Cameras
KW - Compressed sensing
KW - Image reconstruction
KW - Registers
KW - Spatial resolution
KW - Video sequences
UR - http://www.scopus.com/inward/record.url?scp=84951922115&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84951922115&partnerID=8YFLogxK
U2 - 10.1109/CVPRW.2015.7301375
DO - 10.1109/CVPRW.2015.7301375
M3 - Conference contribution
T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
SP - 49
EP - 57
BT - 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2015
PB - IEEE Computer Society
T2 - IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2015
Y2 - 7 June 2015 through 12 June 2015
ER -