Image enhancement for electronic visual prostheses.
This paper briefly describes the framework of artificial human vision systems and identifies several image processing techniques which could enhance the information content of artificially-induced images. We describe our own research in this area, which aims to assess the performance of proposed devices, specifically the usefulness of low quality images associated with electronic visual prostheses. Our subjective assessment studies using representative test patterns have investigated how much information and what types of information are needed to recognise or perceive a scene. 174 normally sighted subjects viewed a set of low quality (low spatial resolution and low grey-scale) static images. Results from this testing has identified informative image processing operations which lead to improved understanding of picture content.
Boyle
J R
JR
Research Concentration in Speech, Audio and Video Technology, School of Electrical and Electronic Systems Engineering, Queensland University of Technology, Brisbane, Australia. jr.boyle@qut.edu.au
Maeder
A J
AJ
Boles
W W
WW
D000465:Algorithms; D001766:Blindness / Q000534:rehabilitation*; D006801:Humans; D007089:Image Enhancement / Q000295:instrumentation / Q000379:methods*; D010363:Pattern Recognition, Automated; D010364:Pattern Recognition, Visual / Q000502:physiology*; D019736:Prostheses and Implants; D011474:Prosthesis Design / Q000295:instrumentation / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012682:Sensory Aids; D014785:Vision, Ocular / Q000502:physiology*