Enhanced-resolution image restoration from a sequence of low-frequency vibrated images by use of convex projections

An algorithm to increase the spatial resolution of digital video sequences captured with a camera that is subject to mechanical vibration is developed . The blur caused by vibration of the camera is often the primary cause for image degradation. We address the degradation caused by low-frequency vibr ations (vibrations for which the exposure time is less than the vibration p eriod). The blur caused by low-frequency vibrations differs from other type s by having a random shape and displacement. The different displacement of each frame makes the approach used in superresolution (SR) algorithms suita ble for resolution enhancement. However, SR algorithms that were developed for general types of blur should be adapted to the specific characteristics of low-frequency vibration blur. We use the method of projection onto conv ex sets together with a motion estimation method specially adapted to low-f requency vibration blur characteristics. We also show that the random blur characterizing low-frequency vibration requires selection of the frames pri or to processing. The restoration performance as well as the frame selectio n criteria is dependent mainly on the motion estimation precision. (C) 2001 Optical Society of America.