Implementing Contourlet Transform for Medical Image Fusion on a Heterogenous Platform

The classic wavelet transform has been applied in registration and fusion of medical images for decades. An extension namely, contourlet transform recently indicated its advantages in image fusion with better efficiency in multi-resolution and multi-direction representation and calculation. However, the even higher computational complexity it requires turns out to be a disastrous concern in embedded applications. In this paper, we implement an acceleration system on a heterogeneous TI Da Vinci dual core processor consisting of an ARM processor core and a DSP processor core. The ARM core controls the fusion procedure by extracting the luminance bits and invoking the DSP core to carry out the time-consuming part of the contourlet transform. The partitions of tasks are determined after the program is analyzed and profiled at functional level to make full use of the computational capability of the heterogeneous platform. Initial measured improved performance results are obtained and analyzed with projected further improvements.