  Background and aim: Surgical telepresence using augmented perception has been
applied, but mixed reality is still being researched and is only theoretical.
The aim of this work is to propose a solution to improve the visualization in
the final merged video by producing globally consistent videos when the
intensity of illumination in the input source and target video varies.
Methodology: The proposed system uses an enhanced multi-layer visualization
with illumination-aware gradient mixing using Illumination Aware Video
Composition algorithm. Particle Swarm Optimization Algorithm is used to find
the best sample pair from foreground and background region and image pixel
correlation to estimate the alpha matte. Particle Swarm Optimization algorithm
helps to get the original colour and depth of the unknown pixel in the unknown
region. Result: Our results showed improved accuracy caused by reducing the
Mean squared Error for selecting the best sample pair for unknown region in 10
each sample for bowel, jaw and breast. The amount of this reduction is 16.48%
from the state of art system. As a result, the visibility accuracy is improved
from 89.4 to 97.7% which helped to clear the hand vision even in the difference
of light. Conclusion: Illumination effect and alpha pixel correlation improves
the visualization accuracy and produces a globally consistent composition
results and maintains the temporal coherency when compositing two videos with
high and inverse illumination effect. In addition, this paper provides a
solution for selecting the best sampling pair for the unknown region to obtain
the original colour and depth.
