Multidimensional Multiscale Parser (MMP) algorithms
have consistently achieved better compression gains
over the years, and recently proposed techniques outperformed
state-of-the-art transform-based image encoders like
the JPEG2000 and H.264/AVC, for both smooth and nonsmooth
images, at low to medium compression rates.
The use of dictionary update tools and a highly adaptable segmentation
feature allowed the encoder to compress images in
a more efficient manner, but the good performance came at
the cost of greater computational cost.
In this paper we address the algorithm complexity, revise
some developments towards reducing the computational
burden and propose a new fast implementation, with little
decrease in coding gain. Experimental results show that
the modified algorithm is still outperforming JPEG2000 and
H.264 for smooth and compound images, with a significant
gain in coding time.