lightness filtering in color images with respect to the gamut school of electrical engineering and...

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Lightness filtering in Lightness filtering in color images with respect color images with respect to the gamut to the gamut School of Electrical Engineering and Computer Science School of Electrical Engineering and Computer Science Kyungpook National Univ. Kyungpook National Univ. Fourteenth Color Imaging Conference Fourteenth Color Imaging Conference Judith Dijk and Piet W. Verbeek Judith Dijk and Piet W. Verbeek Presented by Soo-Jin Sung

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3 /18  A difference between grey images and color images –Grey images Having a simple scale between black and white –Color images The range of colors  Proposed method –A generic method Appling grey image processing on the luminance of color images Without exceeding the limits of the output gamut Introduction

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Page 1: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

Lightness filtering in color images Lightness filtering in color images with respect to the gamutwith respect to the gamut

School of Electrical Engineering and Computer Science School of Electrical Engineering and Computer Science Kyungpook National Univ.Kyungpook National Univ.

Fourteenth Color Imaging ConferenceFourteenth Color Imaging ConferenceJudith Dijk and Piet W. VerbeekJudith Dijk and Piet W. Verbeek

Presented by Soo-Jin Sung

Page 2: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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AbstractAbstract

Proposed method– A generic method that allows grey image processing for

lightness processing on color images • without exceeding the limits of the gamut of the technique or device

The results of the proposed method– Sharpening improvement– Contrast improvement

Page 3: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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A difference between grey images and color images– Grey images

• Having a simple scale between black and white

– Color images• The range of colors

Proposed method– A generic method

• Appling grey image processing on the luminance of color images• Without exceeding the limits of the output gamut

IntroductionIntroduction

Page 4: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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The base– Image processing of color images

• Hue, chroma or saturation, and lightness

– The constraint• The colors of the input image are located within the gamut• Definition for colors as points in the CIELAB space

The generic methodThe generic method

Page 5: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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The desired lightness correction– The move way of the original color point along a fixed path in a

constant hue plane – The path

• The color of the original point ( position in the gamut and the relation between the lightness and chroma change)

• The fixed hue of the point• Keeping the same chroma before and after the image processing

– The prevention of the colorfulness of the image

Figure 1. Illustration of a path for a given point x with chroma constant.

Page 6: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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The effect– The lightness values are distributed nonlinearity over the range– Contrast improvement

– • More contrast in the higher colors, and decreased mean lightness

– • More contrast in the darker colors, and increased mean lightness

Gamma manipulationGamma manipulation

.*)( *min

*max

*min

**min

*max

*min

*

LLLLLLLLout

1

(1)

where : Input and output lightness : The minimum and maximum of the lightness range

**outLandL*max

*min LandL

1

Page 7: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

77 /18 /18

Figure 2. Gamma manipulation.

Figure 3. Gamma manipulation, while keeping chroma constant. (a) the normal, not gamut-limited, gamma manipulation (b) the gamma manipulation as defined in equation 1

Page 8: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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Possible recipes–

• The manipulated lightness while keeping the chroma constant

– • The manipulated lightness while keeping the ratio constant

– Mapping towards black and white • Movement toward black for a lightness decrease• Movement toward white for a lightness increase

– Mapping away from black and white• Movement away from black for a lightness increase• Movement away from white for a lightness decrease

Recipes for gamut-limited gamma Recipes for gamut-limited gamma manipulationmanipulation

** / LCconstant/ ** LC

*C

constant* C

Page 9: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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(a) constant/ ** LCconstant* C (b)

(c) Mapping towards black and white

(d) Mapping away from black and white

Figure 4. Paths along which a color point may move within the constant hue plane, when applying different recipes for gamma manipulations.

Page 10: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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In figure 5– Clipped out-of-gamut pixels– For low gamma values, too yellow in a skin color

In figure 6– Having the smaller effect, because the mean lightness change is smaller– The more natural skin tones than the figure 5

Results for gamut-limited Results for gamut-limited gamma manipulationgamma manipulation

Figure 5. The result for normal gamma manipulation

Figure 6. The results for the recipe.

constant* C

Page 11: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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In figure 7– chroma increase, chroma decrease– Having the somewhat less quality than the images in figure 6

In figure 8– mixed white, mixed black– Less vivid and less than quality of other recipes

In figure 9– No difference very much from each other

1

Figure 9. The results for the away from black recipe.

Figure 8. The results for the mapping towards black recipe.

Figure 7. The results for the recipe.

constant/ ** LC

1

1 1

Page 12: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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~

~~~

~~~

)(

1)( IFII

IIFinverseRhighinverse

inverseb

Process of sharpening

– Changing the lightness of a point– Adding a high frequency filtered version of the image to the original image– Used unsharp masking

• The high frequency filtered version

• The unsharp masking sharpening filter

• Inverse unsharp masking filter

Gamut limited sharpeningGamut limited sharpening

highR IIIF~~~~

)(

~~~~~),(1 IFIIGI highhigh

(2)

(3)

where ~ : the fourier transform

(4)

Page 13: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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Tested recipes– Sharpening within the gamut

• The maximum and minimum sharpening for each point within the gamut

– Gamut limited sharpening• The desired lightness difference adjusted so that the maximum

lightness difference• Adjustment of the value of

– Mapping towards black and white• Selection of the new point through the original point and white

or black

– Mapping halfway towards black and white– Mapping away from black and white

Recipes for gamut-limited Recipes for gamut-limited sharpeningsharpening

)0( * L)0( * L

Page 14: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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Figure 10. Different paths for sharpening manipulation.

Page 15: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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Figure 11. The result for the different recipes (a-e). The original image is smoothed with inverse unsharp masking with . The sharpening algorithm is unsharp masking with and . 6.0

6.0inverse1

Results for gamut-limited Results for gamut-limited sharpeningsharpening

Page 16: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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The sharpest images ((b) and (d))– The effect on the location of the eyes and the mouth– The more colorful image (b) than the image (d)

• The quite visible chroma change in the low frequency for the (d)

(e) recipe– Adding chroma on places where the lightness is changed

• More colorful than the colors in the original image

– In the colors of the mouth of the woman

Page 17: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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Figure 13. The result for mapping towards black and white (c) for different values of , with . 1

(a) and (c) recipe and the normal sharpening– Adjustment of the size of for these recipes by the user– Having somewhat “greyish” results for– Shift towards the achromatic axis in proportion to – Causing a chroma reduction for all points ((c) recipe)

Figure 12. The result for sharpening within the gamut (a) for different values of , with . 1

6.0

Page 18: Lightness filtering in color images with respect to the gamut School of Electrical Engineering and Computer Science Kyungpook National Univ. Fourteenth

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Proposed method– A generic method that allows grey image processing for lightn

ess processing on color images • Without affecting color rendering• Staying within the gamut of the apparatus in question

Results– Sharpening improvement

• The chroma change in proportion to the lightness• Improvement for the most images

– Contrast improvement• The chroma reduction in proportion to the lightness difference

– Mapping towards black and white recipe

• The chroma increase in proportion to the lightness difference– Mapping away from black and white recipe

ConclusionsConclusions