Searching for the optimal curvelet tiling

Curvelets were recently introduced as a popular extension of wavelets. In the curvelet domain the input image is represented by sets of coefficients representing signal energy in different scales and angular directions. In this paper an algorithm that searches for optimal tilings for use with the curvelet transform is introduced. We consider two adaptations: scale locations, and the number of angular divisions per scale. A search algorithm that searches for the optimal tiling with respect to denoising performance is introduced. Results show significant improvement over original curvelet tilings. Tiling results were also tested with a seismic compressed sensing recovery problem. A similar performance advantage is reported.