Abstract: In an image processing method, a first two-dimensional image (I(x, y)) of a three-dimensional scene is obtained. Each pixel location of a first image is associated with a respective distance parameter (z(x, y)) representing a distance of a viewer's eye to an object of the scene appearing at this pixel location in the first image. A respective spreading parameter (?d(x, y)) is determined for each pixel location as a function of the distance parameter associated with this pixel location, of a dioptric power (Pcorr) of a portion of a correction lens simulated as placed along a ray extending between the viewer's eye and the object of the scene appearing at said pixel location in the first image, and of a simulated maximum accommodation power (Pacc) of the viewer's eye. A second, blurred two-dimensional image (I?(x, y)) is generated from the first image using a local convolution kernel varying across the image. This kernel can be made sparse, i.e.

Abstract: In an image processing method, a first two-dimensional image (I(x, y)) of a three-dimensional scene is obtained. Each pixel location of a first image is associated with a respective distance parameter (z(x, y)) representing a distance of a viewer's eye to an object of the scene appearing at this pixel location in the first image. A respective spreading parameter (?d(x, y)) is determined for each pixel location as a function of the distance parameter associated with this pixel location, of a dioptric power (Pcorr) of a portion of a correction lens simulated as placed along a ray extending between the viewer's eye and the object of the scene appearing at said pixel location in the first image, and of a simulated maximum accommodation power (Pacc) of the viewer's eye. A second, blurred two-dimensional image (I?(x, y)) is generated from the first image using a local convolution kernel varying across the image. This kernel can be made sparse, i.e.