Statistics – Applications
Scientific paper
Dec 1991
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1991spie.1567..659n&link_type=abstract
Proc. SPIE Vol. 1567, p. 659-669, Applications of Digital Image Processing XIV, Andrew G. Tescher; Ed.
Statistics
Applications
Scientific paper
Transformation of the image motion vector to a different domain exhibits impressive properties, such as resistance to noise and reduction in computational time and storage requirements. Using the steepest ascent algorithm in a transformed domain, we develop an iterative technique for frame-to-frame image motion estimation. The estimator seeks for the maximum likelihood (ML) estimate of the transformed-coefficients of the motion field. The scheme is implemented using discrete cosine, discrete sine, slant, Hadamard-Walsh, and Haar transforms. Since the motion field is generally slowly-varying, it is shown that by ignoring the higher number transformed-coefficients, substantial improvement in noise reduction is achieved. Simulation experiments are performed to indicate the validity of the analysis for real images in the presence of noise. Results of the simulations are presented.
Lipp John I.
Namazi Nader M.
No associations
LandOfFree
Nonuniform image motion estimation in transformed-domain does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Nonuniform image motion estimation in transformed-domain, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Nonuniform image motion estimation in transformed-domain will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1269056