Deconvolution of adaptive optics retinal images.
We quantitatively demonstrate the improvement to adaptively corrected retinal images by using deconvolution to remove the residual wave-front aberrations. Qualitatively, deconvolution improves the contrast of the adaptive optics images. In this work we demonstrate that quantitative information is also increased by investigation of the improvement to cone classification due to the reduction in confusion of adjacent cones because of the extended wings of the point-spread function. The results show that the error in classification between the L and M cones is reduced by a factor of 2, thereby reducing the number of images required by a factor of 4.
Center for Adaptive Optics, University of California, Santa Cruz, California 95064, USA. christou@ucolick.org
Julian C
JC
Christou
Austin
A
Roorda
David R
DR
Williams
D000465:Algorithms; D000818:Animals; D015350:Contrast Sensitivity / Q000502:physiology; D008251:Macaca; D055095:Optics and Photonics; D012160:Retina / Q000502:physiology*; D017949:Retinal Cone Photoreceptor Cells / Q000502:physiology