Stereographic Combing a Porcupine

or

Studies on Orientation Diffusion

Nir A. Sochen, Chen Sagiv, Ron Kimmel

In this page the color figures appearing in the manuscript are presented.

Figure 6.1

 

Two vector fields before (left) and after (right) the

flow on S1.

Figure 6.2

 

 

The colors are restricted to one quarter of the upper hemisphere defined around the black point in the RGB space.

 

 

The original image (left), the noisy image (middle), and the filtered image (right).

 

The vector fields of part of the images, before (left) and after (right) the flow.

Figure 6.3

 

The HSV color model captures human color perception better than the RGB model which is the common way our machines represent colors.

 

 

The original image (left), the noisy image (middle) and the filtered image (right) demonstrate the effect of the flow as a denoising filter in the HSV color space.

Figure 6.4

 

An example for stereographic orientation diffusion used in the HSV color space. The original image (left), the noisy image (middle) and the filtered image (right) demonstrate the effect of the flow as a denoising filter in the HSV color space when using stereographic coordinates.

Figure 7.13

a. The original noise-free image (left). b. The image after random noise was added (right).

Figure 7.14

a. The result of Linear diffusion (left). b. The result of TV diffusion (right).

Figure 7.15

a. The result of HP diffusion for b = 10-5 (left). b. The result of HP diffusion for b = 10 (right).

Figure 7.16

a. The result of SP diffusion for b = 10-3 (left). b. The result of SP diffusion for b = 10 (right).

 

 

 

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Last Modified: Thursday, 10 October 2002