Improved fast block matching algorithm in feature domain

A fast block matching algorithm in the feature domain was proposed by Fok and Au with a computation reduction factor of N/2 for a search block size of N×N. Although the algorithm can achieve close-to-optimal result, it requires a large amount of memory to store the features. This paper presents three improved fast block matching algorithms in the integral projections feature domain which can also reduce the computation significantly but with a considerably lower memory requirement. With a search block size of N×N, two of our algorithms retain a computation reduction factor of N/2 while the other one can achieve a computation reduction factor of N. The three algorithms can achieve close-to-optimal performance in mean absolute difference(MAD) sense.