Benefits of hybrid DCT domain image matching
R. Reeves, Kurt Kubik · ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences · 2000
An enhancement to least squares image matching is proposed which combines a Discrete Cosine Transform (DCT) domain solution of the linearized normal equations, and resampling between iterations in the pixel domain. This approach reduces the size of the normal equations by discarding higher frequency DCT coefficients, while avoiding the overhead of image resampling in the DCT domain. A method for computing the DCT of the sampled derivative of a function from the DCT of its samples is given, and the least squares problem is framed in the DCT domain. In an experimental comparison between the proposed algorithm and an equivalent pixel domain algorithm, we find that the match time can be halved for 32 × 32 pixel windows, and reduced to 75% for 16 × 16 windows, while measures of match quality remain comparable or improve. The measures of much quality considered were the mean and standard deviation of the disparity error, and the number of match windows that converged. The optimum percentages of DCT coefficients for these window sizes were 20% for the 16 × 16 window and 10% for the 32 × 32 window. An 8 × 8 window size was also tested, but showed no speed-up over the pixel domain algorithm. The approach incorporates derivative estimates that result in better accuracy than can be achieved using the first differences of a pixel domain approach.