Sushanth G. Sathyanarayana¹, Ankit A. Bhurane² and Shankar M.Venkatesan¹, ¹Philips Research India, India and ²Indian Institute of Technology - Mumbai, India

Video Stabilization, which is important for better analysis and user experience, is typically done through Global Motion Estimation (GME) and Compensation. GME can be done in image domain using many techniques or in Transform domain using the well-known Phase Correlation methods which relate motion to phase shift in the spectrum. While image domain methods are generally slower (due to dense vector field computations), they can do global as well as local motion estimation. Transform domain methods cannot normally do local motion, but are faster and more accurate on homogeneous images, and are resilient to even rapid illumination changes and large motion. However both these approaches can become very time consuming if one needs more accuracy and smoothness because of the nature of the tradeoff. We show here that wavelet transforms can be used in a novel way to achieve a very smooth stabilization along with a significant speedup in this Fourier domain computation without sacrificing accuracy. We do this by adaptively selecting and combining motion computed on a specific pair of sub-bands using the wavelet interpolation capability. Our approach yields a smooth, scalable, fast and adaptive algorithm (based on time requirement and recent motion history) to yield significantly better accuracy than a single level wavelet decomposition based approach.