"Foveated imaging is a digital image processing technique in which the image resolution, or amount of detail, varies across the image according to one or more "fixation points." A fixation point indicates the highest resolution region of the image and corresponds to the center of the eye's retina, the fovea."
I want to use such image to illustrate humans visual acuity, The bellow diagram shows the relative acuity of the left human eye (horizontal section) in degrees from the fovea (Wikipedia) :
Is there a way to create a foveated image in Mathematica using its image processing capabilities ?
Something along the following lines may work for you. The filtering details should be adjusted to your tastes.
lena = ExampleData[{"TestImage", "Lena"}]
ImageDimensions[lena]
==> {512, 512}
mask = DensityPlot[-Exp[-(x^2 + y^2)/5], {x, -4, 4}, {y, -4, 4},
Axes -> None, Frame -> None, Method -> {"ShrinkWrap" -> True},
ColorFunction -> GrayLevel, ImageSize -> 512]
Show[ImageFilter[Mean[Flatten[#]] &, lena, 20, Masking -> mask], ImageSize -> 512]
Following on Sjoerd's answer, you can Fold[]
a radius-dependent blur as follows.
A model for the acuity (very rough model):
Clear[acuity];
acuity[distance_, x_, y_, blindspotradius_] :=
With[{\[Theta] = ArcTan[distance, Sqrt[x^2 + y^2]]},
Clip[(Chop@Exp[-Abs[\[Theta]]/(15. Degree)] - .05)/.95,
{0,1}] (1. - Boole[(x + 100.)^2 + y^2 <= blindspotradius^2])]
Plot3D[acuity[250., x, y, 25], {x, -256, 256}, {y, -256, 256},
PlotRange -> All, PlotPoints -> 40, ExclusionsStyle -> Automatic]
The example image:
size = 100;
lena = ImageResize[ExampleData[{"TestImage", "Lena"}], size];
Manipulate[
ImageResize[
Fold[Function[{ima, r},
ImageFilter[(Mean[Flatten[#]] &), ima,
7*(1 - acuity[size*5, r, 0, 0]),
Masking -> Graphics[Disk[p/2, r],
PlotRange -> {{0, size}, {0, size}}]
]],
lena, Range[10, size, 5]],
200],
{{p, {size, size}}, Locator}]
Some examples:
WaveletMapIndexed
can give a spatially-varying blur, as shown in the Mathematica documentation (WaveletMapIndexed->Examples->Applications->Image Processing). Here is an implementation of a foveatedBlur
, using a compiled version of the acuity
function from the other answer:
Clear[foveatedBlur];
foveatedBlur[image_, d_, cx_, cy_, blindspotradius_] :=
Module[{sx, sy},
{sy, sx} = ImageDimensions@image;
InverseWaveletTransform@WaveletMapIndexed[ImageMultiply[#,
Image[acuityC[d, sx, sy, -cy + sy/2, cx - sx/2, blindspotradius]]] &,
StationaryWaveletTransform[image, Automatic, 6], {___, 1 | 2 | 3 | 4 | 5 | 6}]]
where the compiled acuity is
Clear[acuityC];
acuityC = Compile[{{distance, _Real}, {sx, _Integer}, {sy, _Integer}, {x0, _Real},
{y0, _Real}, {blindspotradius, _Real}},
Table[With[{\[Theta] = ArcTan[distance, Sqrt[(x - x0)^2 + (y - y0)^2]]},
(Exp[-Abs[\[Theta]]/(15 Degree)] - .05)/.95
*(1. - Boole[(x - x0)^2 + (y - y0 + 0.25 sy)^2 <= blindspotradius^2])],
{x, Floor[-sx/2], Floor[sx/2 - 1]}, {y, Floor[-sy/2], Floor[sy/2 - 1]}]];
The distance parameter sets the rate of falloff of the acuity. Focusing point {cx,cy}
, and blind-spot radius are self-explanatory. Here is an example using Manipulate
, looking right at Lena's right eye:
size = 256;
lena = ImageResize[ExampleData[{"TestImage", "Lena"}], size];
Manipulate[foveatedBlur[lena, d, p[[1]], p[[2]], 20], {{d, 250}, 50,
500}, {{p, ImageDimensions@lena/2}, Locator, Appearance -> None}]
See the blind spot?