Space/error tradeoffs for lossy wavelet reconstruction
Jonathan Frain, R. Daniel Bergeron · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
Discrete Wavelet Transforms have proven to be a very effective tool for compressing large data sets. Previous research has sought to select a subset of wavelet coefficients based on a given space constraint. These approaches require non-negligible overhead to maintain location information associated with the retained coefficients. Our approach identifies entire wavelet coefficient subbands that can be eliminated based on minimizing the total error introduced into the reconstruction. We can get further space reduction (with more error) by encoding some or all of the saved coefficients as a byte index into a floating point lookup table. We demonstrate how our approach can yield the same global sum error using less space than traditional MR implementations.