  Tissue oxygenation and perfusion can be an indicator for organ viability
during minimally invasive surgery, for example allowing real-time assessment of
tissue perfusion and oxygen saturation. Multispectral imaging is an optical
modality that can inspect tissue perfusion in wide field images without
contact. In this paper, we present a novel, fast method for using RGB images
for MSI, which while limiting the spectral resolution of the modality allows
normal laparoscopic systems to be used. We exploit the discrete Haar
decomposition to separate individual video frames into low pass and directional
coefficients and we utilise a different multispectral estimation technique on
each. The increase in speed is achieved by using fast Tikhonov regularisation
on the directional coefficients and more accurate Bayesian estimation on the
low pass component. The pipeline is implemented using a graphics processing
unit (GPU) architecture and achieves a frame rate of approximately 15Hz. We
validate the method on animal models and on human data captured using a da
Vinci stereo laparoscope.
