PT Unknown
AU Olivier Penacchio
   Laura Dempere-Marco
   Xavier Otazu
TI Switching off brightness induction through induction-reversed images
BT Perception
PY 2012
BP 208
VL 41
AB Brightness induction is the modulation of the perceived intensity of anarea by the luminance of surrounding areas. Although V1 is traditionally regarded asan area mostly responsive to retinal information, neurophysiological evidencesuggests that it may explicitly represent brightness information. In this work, weinvestigate possible neural mechanisms underlying brightness induction. To this end,we consider the model by Z Li (1999 Computation and Neural Systems10187-212)which is constrained by neurophysiological data and focuses on the part of V1responsible for contextual influences. This model, which has proven to account forphenomena such as contour detection and preattentive segmentation, shares withbrightness induction the relevant effect of contextual influences. Importantly, theinput to our network model derives from a complete multiscale and multiorientationwavelet decomposition, which makes it possible to recover an image reflecting theperceived luminance and successfully accounts for well known psychophysicaleffects for both static and dynamic contexts. By further considering inverse problemtechniques we define induction-reversed images: given a target image, we build animage whose perceived luminance matches the actual luminance of the originalstimulus, thus effectively canceling out brightness induction effects. We suggest thatinduction-reversed images may help remove undesired perceptual effects and canfind potential applications in fields such as radiological image interpretation
ER