Table 1 Image slope constants and contrasts.

From: A higher order visual neuron tuned to the spatial amplitude spectra of natural scenes

Figure

Image

α

Contrast (electrophysiology)

Contrast (behaviour)

1, 2, 5

Hill

1.0731

0.1346

 

1, 2, 5

Outdoor

1.2142

0.1018

 

1, 2, 5

Rockgarden

0.9978

0.0692

 

1, 2, 5

Shadow

1.1619

0.1196

 

1, 2, 5

Tree

1.0845

0.0976

 

1–2

Random noise

1.8024

0.0830

 

3–4

Random noise

0.0001

0.1618

 

3–4

Random noise

1.0000

0.1232

 

3–4

Random noise

1.9982

0.1261

 

3–4

Hill

0.0003

0.1086

 

3–4

Hill

1.0000

0.1290

 

3–4

Hill

1.9994

0.1437

 

3–4

Shadow

−0.0006

0.0846

 

3–4

Shadow

1.0000

0.1136

 

3–4

Shadow

1.9993

0.1375

 

6

Random panorama

0.4110

 

0.1428

6

Random panorama

0.8276

 

0.1208

6

Random panorama

1.2505

 

0.1255

6

Random panorama

1.6625

 

0.1637

6

Bushes panorama

0.3881

 

0.0924

6

Bushes panorama

0.7719

 

0.1186

6

Bushes panorama

1.1820

 

0.1592

6

Bushes panorama

1.5644

 

0.1710

  1. RMS, root-mean square.
  2. The data show the slope constants (α’s) and the effective RMS contrasts of the images used in the study. For analysis we used the part of the image seen by the hoverfly. The slope constant (image α) was calculated by polynomial fitting between 0.06–1 c.p.d. The effective RMS contrast for the images used in electrophysiology was calculated after bandpass filtering the images between 0.06–1 c.p.d. The effective RMS contrast for the images used in behaviour was calculated after low-pass filtering the images from 1 c.p.d.
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