s_HumanSceneStatistics

We create a random (Gaussian, white spatial noise, D65 SPD) scene. We visualize the white noise spatial statistics in the scene space.

Then we pass this scene through the human optics to create a spectral irradiance image.

Finally, we compute the responses in the cones, using three simplified human sensors. Each mosaic comprises a full mosaic of each of the cone types. We show amplitude of the spatial FFT of the cone mosaic absorptions for the L,M, and S cone types.

All of the three types experience a low spatial frequency response because of the lens. The S-cone mosaic only experiences a relatively low spatial frequency image.

Initialize
We start with a small (2 deg) scene of white noise
The amplitude of the spatial contrast of the radiance image
Create the optical image. Notice that it is significantly blurred
Set up the human sensor parameters and compute.
Plot the three spatial amplitude spectra

if isempty(which('Lens'))
    fprintf('%s requires ISETBio (Lens).',mfilename);
    return;
end

s_humanSceneStatistics requires ISETBio (Lens).

Initialize

ieInit

We start with a small (2 deg) scene of white noise

Each radiance is drawn from a Gaussian

contrast = 0.5;
scene =  sceneCreate('white noise',[256 256],contrast);
scene = sceneSet(scene,'h fov',2);
sceneWindow(scene);

The amplitude of the spatial contrast of the radiance image

This is a white noise image, so the amplitude spectrum is flat. Notice that the contrast means we have removed the mean. We plot the radiance data at 550 nm, but this would be the same at any wavelength.

scenePlot(scene,'radiance fft image',550);

Create the optical image. Notice that it is significantly blurred

This is because of the human optics

oi = oiCreate('human');
oi = oiCompute(oi,scene);
oiWindow(oi);

Set up the human sensor parameters and compute.

We will create a series of sensors, each with just one of the three types of cones. For each, we will compute the spatial mosaic of responsea, and then plot the spatial amplitude spectrum

params.sz = [256,256];
params.coneAperture = [2 2 ]*1e-6;     % In meters
xy = [64,1];
cType = {'L','M','S'};
pFFT = cell(3,1); sensor = cell(3,1);
for ii=1:3
    params.rgbDensities = [0 0 0 0]; % Empty, L,M,S
    params.rgbDensities(ii+1) = 1;   % Fill up with L,M or S.

    sensor{ii} = sensorCreate('human',[],params);

    sensor{ii} = sensorSet(sensor{ii},'exp time',0.2);
    sensor{ii} = sensorCompute(sensor{ii},oi);
    vcAddAndSelectObject(sensor{ii});

    p = sensorGet(sensor{ii},'electrons');
    p = reshape(p,params.sz(1),params.sz(2));
    p = p - mean(p(:));  % Remove mean
    pFFT{ii} = fftshift(abs(fft2(p)));  % Compute FFT
end

Plot the three spatial amplitude spectra

ieNewGraphWin([],'tall');
for ii=1:3
    subplot(3,1,ii)
    imagesc(pFFT{ii}); colormap(hot(64)); colorbar;
    axis image; axis off
    xlabel('Cycles/deg'); ylabel('Cycles/deg');
    title(sprintf('%s cone spatial amp spectrum',cType{ii}));
    %          hold on;
    %          sz = size(pFFT{ii});
    %          x = linspace(0,sz(1),sz(1));
    %          y = (1 - ieScale(sum(pFFT{ii}),1))*sz(2);
    %          plot(x,mean(pFFT{ii}),'b-');
end