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.
© 2004 Optical Society of America
(100.1830) Image processing : Deconvolution
(100.2980) Image processing : Image enhancement
(100.3190) Image processing : Inverse problems
(170.4470) Medical optics and biotechnology : Ophthalmology
Julian C. Christou, Austin Roorda, and David R. Williams, "Deconvolution of adaptive optics retinal images," J. Opt. Soc. Am. A 21, 1393-1401 (2004)