  It is generally accepted that human vision is an extremely powerful
information processing system that facilitates our interaction with the
surrounding world. However, despite extended and extensive research efforts,
which encompass many exploration fields, the underlying fundamentals and
operational principles of visual information processing in human brain remain
unknown. We still are unable to figure out where and how along the path from
eyes to the cortex the sensory input perceived by the retina is converted into
a meaningful object representation, which can be consciously manipulated by the
brain. Studying the vast literature considering the various aspects of brain
information processing, I was surprised to learn that the respected scholarly
discussion is totally indifferent to the basic keynote question: "What is
information?" in general or "What is visual information?" in particular. In the
old days, it was assumed that any scientific research approach has first to
define its basic departure points. Why was it overlooked in brain information
processing research remains a conundrum. In this paper, I am trying to find a
remedy for this bizarre situation. I propose an uncommon definition of
"information", which can be derived from Kolmogorov's Complexity Theory and
Chaitin's notion of Algorithmic Information. Embracing this new definition
leads to an inevitable revision of traditional dogmas that shape the state of
the art of brain information processing research. I hope this revision would
better serve the challenging goal of human visual information processing
modeling.
