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

2. 2 /18 Abstract  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

3. 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

4. 4 /18   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 method

5. 5 /18  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.

6. 6 /18  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 manipulation (1) where : Input and output lightness : The minimum and maximum of the lightness range

7. 7 /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

8. 8 /18  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 manipulation

9. 9 /18 (a) (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.

10. 10 /18  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 gamma manipulation Figure 5. The result for normal gamma manipulation Figure 6. The results for the recipe.

11. 11 /18  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 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.

12. 12 /18   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 sharpening (2) (3) where ~ : the fourier transform (4)

13. 13 /18  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 sharpening

14. 14 /18 Figure 10. Different paths for sharpening manipulation.

15. 15 /18 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. Results for gamut-limited sharpening

16. 16 /18  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

17. 17 /18 Figure 13. The result for mapping towards black and white (c) for different values of, with.  (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.

18. 18 /18  Proposed method –A generic method that allows grey image processing for lightness 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 Conclusions