Non-blind hardware and software deconvolution for jitter reduction

For many imaging applications installed on moving platforms, especially for smaller platforms without the advantage of large inertial mass, jitter is one the primary drivers in modulation transfer function (MTF) degradation. The use of an inertial measurement unit (IMU) to detect motion for non-blind deconvolution of imagery is not a new concept. However, most systems are focused on still photographs for small optical systems, such as cell phones, and are not focused on real-time implementation for full motion video (FMV) with dynamic systems that have multiple moving parts. Further, no existing system utilizes IMU information to intelligently decide when a camera system should integrate during the typical 33 ms framerate. Having control over when to integrate and for how long allows for greater signal-to-noise ratios (SNRs) at smaller jitters by selecting times when jitter is minimized based on the LOS motion. This work presents the framework of a jitter mitigation approach that both optimally decides on the integration window and implements non-blind deconvolution to produce a system that provides enhanced image resolution under a variety of conditions