Improving resolution by image registration
CVGIP: Graphical Models and Image Processing
A survey of image registration techniques
ACM Computing Surveys (CSUR)
Limits on Super-Resolution and How to Break Them
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion-Based Motion Deblurring
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
A Unified Approach to Superresolution and Multichannel Blind Deconvolution
IEEE Transactions on Image Processing
A sensor-based approach to linear blur identification for real-time video enhancement
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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The high density image sensors of state-of-the-art imaging systems provide outputs with high spatial resolution, but require long exposure times. This limits their applicability, due to the motion blur effect. Recent technological advances have lead to adaptive image sensors that can combine several pixels together in real time to form a larger pixel. Larger pixels require shorter exposure times and produce high-frame-rate samples with reduced motion blur. This work proposes combining an FPGA with an adaptive image sensor to produce an output of high resolution both in space and time. The FPGA is responsible for the spatial resolution enhancement of the high-frame-rate samples using super-resolution (SR) techniques in real time. To achieve it, this article proposes utilizing the Iterative Back Projection (IBP) SR algorithm. The original IBP method is modified to account for the presence of noise, leading to an algorithm more robust to noise. An FPGA implementation of this algorithm is presented. The proposed architecture can serve as a general purpose real-time resolution enhancement system, and its performance is evaluated under various noise levels.