Digital Image Processing Assignment: Log-Polar and Cortical Image Transformations, Assignments of Digital Signal Processing

An assignment for a digital image processing course at the university of houston, focusing on the log-polar and cortical image transformations. Students are required to write programs to map input images to log-polar space and generate cortical images from retinal images.

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Pre 2010

Uploaded on 08/17/2009

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COSC 4393/6397
Digital Image Processing
Department of Computer Science
University of Houston
Assignment #2
Due: 10/03/07
1. Many artificial vision systems have been motivated by the image sensing
capabilities of biological vision systems. One such mechanism is scene sampling,
motivated by the inherent in the structure of the retina. Photoreceptors in the
retina are distributed to provide high resolution on the central part of the retina
(fovea) with decreasing resolution towards the periphery. This has motivated the
log-polar image geometry.
When compared to the usual cartesian images, the log-polar images allow faster
sampling rates on artificial vision systems without reducing the size of the field of
view. The log-polar transformation is a conformal mapping from the points on the
cartesian plane (x,y) to points in the log-polar plane ():
The mapping is described by:

=log x2+y2
θ=atan y
x
Write a program to map an input image to the log-polar space. For visualization, 
should be a discrete variable. You can achieve this by equating =radius and
ignoring the log operation. sampling should be a free parameter. Test your
code with =64. This should result in a polar image of size 128x64 for an input
image of size 256x256.
2. In recent years, there has been research that supports the hypothesis that there is
further magnification of the foveal region from retina to cortex. Several
researches have measured the cortical magnification factor as a function of retinal
eccentricity. One such measurement is the complex map, C = log(Z + a), that
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COSC 4393/

Digital Image Processing

Department of Computer Science

University of Houston

Assignment

Due: 10/03/

  1. Many artificial vision systems have been motivated by the image sensing capabilities of biological vision systems. One such mechanism is scene sampling, motivated by the inherent in the structure of the retina. Photoreceptors in the retina are distributed to provide high resolution on the central part of the retina (fovea) with decreasing resolution towards the periphery. This has motivated the log-polar image geometry. When compared to the usual cartesian images, the log-polar images allow faster sampling rates on artificial vision systems without reducing the size of the field of view. The log-polar transformation is a conformal mapping from the points on the cartesian plane (x,y) to points in the log-polar plane (): The mapping is described by:  =log x 2 + y 2 θ = a tan y x

⎝⎜^

Write a program to map an input image to the log-polar space. For visualization,  should be a discrete variable. You can achieve this by equating =radius and ignoring the log operation.  sampling should be a free parameter. Test your code with =64. This should result in a polar image of size 128x64 for an input image of size 256x256.

  1. In recent years, there has been research that supports the hypothesis that there is further magnification of the foveal region from retina to cortex. Several researches have measured the cortical magnification factor as a function of retinal eccentricity. One such measurement is the complex map, C = log(Z + a), that

captures the spatial mapping over a large portion of retina and cortex. C is the complex representation of cortical position, Z is for the retinal position, and a is a constant measured to be about 0.3 degrees if Z is measured in degrees and C in millimeters. This formula captures the shape of the flattened cortical surface for one visual hemi-field. If () are the polar retinal coordinates, and (R,TH) are the polar cortical coordinates with fovea at the origin, we can define mapping to be: R = log(+a) TH =  Write a program to generate the retinal image given an input image. In addition, develop a simple user interface that allows for selection of a point in an image and performs the mapping to generate the cortical image.

  1. Test the developed functions with the images provided and report on the results.