In this paper, we present a new algorithm for solving the block
matching problem which is independent of image content and is faster
than other full-search methods. The method employs a novel data
structure called the Windowed-Sum-Squared-Table, and uses the fast
Fourier transform (FFT) in its computation of the sum squared
difference (SSD) metric. Use of the SSD metric allows for higher peak
signal to noise ratios than other fast block matching algorithms which
require the sum of absolute difference (SAD) metric. However, because
of the complex floating point and integer math used in our computation
of the SSD metric, our method is aimed at software implementations
only. Test results show that our method has a running time 13%-29% of
that for the exhaustive search, depending on the size of the search
range.
