# Presentation: 771803

## Color image processing

- Vasile Buzuloiu, Mihai Ciuc
- University “Politehnica” Bucuresti
- Romania

- Fermi Lab - November 2005

## Contents

- Adaptive neighborhood image processing:
- filtering
- enhancement
- Red-eye removal

- Fermi Lab - November 2005

## Principle of adaptive neighborhoods

**The idea**: the use of *adaptive neighborhoods (AN) *to derive the new value of a pixel.
- The AN is:
- Variable-sized, variable-shaped
- connex
- gathers all neighboring pixels that belong to the same statistical distribution as the current pixel (called « seed »)
- Major drawback: the AN must be determined for each image pixel independently

- Fermi Lab - November 2005

## Determination of a pixel’s AN

- The general algorithm [*Rangayyan et al. - 92*]: region growing with respect to the seed *s=(i,j)*.
- The retention criterion:

- Fermi Lab - November 2005

## Problems to work out:
The aggregation criterion:  

Automatic computing of threshold S
S too low: small AN
S too high: AN grows over boundaries
S: related to noise standard deviation
Presence of salt-and-pepper noise
the seed value may be an outlier
the reference value: a robust estimator  (e.g., the marginal median)

- The aggregation criterion:
- Automatic computing of threshold *S*
*S* too low: small AN
*S* too high: AN grows over boundaries
*S*: related to noise standard deviation
- Presence of salt-and-pepper noise
- the seed value may be an outlier
- the reference value: a robust estimator  (e.g., the marginal median)

- AN color filter

- Fermi Lab - November 2005

## AN color filter

- Solution : two steps AN determination:
- 1st step: rough determination
- Region growing with moderate threshold
- criterion:
- 2nd step: refining the AN statistics
- Only background pixels *f *are reinspected:
- criterion:
- Results:

- Fermi Lab - November 2005

## Color image filtering

- The filtered seed value: the vectorial LLMMSE.
- matrice **A** and vector **b **are sought such as

- Result:

- Fermi Lab - November 2005

## Color image filtering - results

- Fermi Lab - November 2005

## Color image enhancement

- Histogram equalization (HE):
- developed for scalar images
- aims at compensating for the illumination defects
- major advantage: automatical operator
- Color HE:
- difficulties related to the vectorial nature of the data
- two classes of methods:
*RGB*:* *poor control over shifts in hue
- perceptual spaces (e.g, *HSI*): separation between perceptual components

- Fermi Lab - November 2005

## Principle of AN HE:

- Hue preservation:
- intensity only is processed
- Increasing of number of colors:
- taking into account of spatial neighborhood
- Neighborhood uniformity:
- adaptive determination
- Balanced overall luminosity:
- use of the global HE function (or of any other luminosity modifying function, e.g., automatic contrast stretching)

- Fermi Lab - November 2005

## ANHE steps

- Computing the intensity image *I*
- Computing the golbal HE function of *I: F**I*
- For each pixel in *I*:
- Determination of an AN according to: |*g*(*p*)-*g*(*s*)|<*S*
- shifting *h**AN* such as ***AN*  *F**I*(***AN*)
- spreading of *h**AN* proportionally to ***AN*
*modification of seed’s intensity only*
- Result: a both *global *and *local *procedure*!*

- Fermi Lab - November 2005

## Results

- Fermi Lab - November 2005

## Automatic correction of red-eye defect  

- Disturbing effect characteristic for indoor pictures taken with the flash on.

- Fermi Lab - November 2005

## Red-eye effect

- Cause: reflection of the light beam on the retina, which is highly vasculzarized.
- Correction:
- manual: the user must manually select the eye
- automatic: difficult, given the imposed constraints:
- reduced processing time
- low incidence of false positives

- Fermi Lab - November 2005

## Red-eye effect

- Red-eye characteristics:
*Redness*: must be assessed in an appropriate color space
*Roundness*
*Localized on human faces:*
- Face detection algorithms are not advised:
- Poor performances
- Increased processing time
- The problem must be tackled from a different point of view
- Correction: “redness” reduction

- Fermi Lab - November 2005

## Red-eye effect: results

- Fermi Lab - November 2005

## Red-eye effect: results

- Fermi Lab - November 2005