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Correction of Clipped Pixels in Color Images
March 2011 (vol. 17 no. 3)
pp. 333-344
ASCII Text
x 
 
Di Xu, Colin Doutre, Panos Nasiopoulos, "Correction of Clipped Pixels in Color Images," IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 3, pp. 333-344, March, 2011.
 
 
BibTex
x
 
@article{ 10.1109/TVCG.2010.63,
author = {Di Xu and Colin Doutre and Panos Nasiopoulos},
title = {Correction of Clipped Pixels in Color Images},
journal ={IEEE Transactions on Visualization and Computer Graphics},
volume = {17},
number = {3},
issn = {1077-2626},
year = {2011},
pages = {333-344},
doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2010.63},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Visualization and Computer Graphics
TI - Correction of Clipped Pixels in Color Images
IS - 3
SN - 1077-2626
SP333
EP344
EPD - 333-344
A1 - Di Xu,
A1 - Colin Doutre,
A1 - Panos Nasiopoulos,
PY - 2011
KW - Clipping
KW - desaturation
KW - color restoration
KW - high dynamic range (HDR)
KW - inverse tone mapping.
VL - 17
JA - IEEE Transactions on Visualization and Computer Graphics
ER -
 
Di Xu, University of British Columbia, Vancouver, BC
Colin Doutre, University of British Columbia, Vancouver, BC
Panos Nasiopoulos, University of British Columbia, Vancouver, BC
Conventional images store a very limited dynamic range of brightness. The true luma in the bright area of such images is often lost due to clipping. When clipping changes the R, G, B color ratios of a pixel, color distortion also occurs. In this paper, we propose an algorithm to enhance both the luma and chroma of the clipped pixels. Our method is based on the strong chroma spatial correlation between clipped pixels and their surrounding unclipped area. After identifying the clipped areas in the image, we partition the clipped areas into regions with similar chroma, and estimate the chroma of each clipped region based on the chroma of its surrounding unclipped region. We correct the clipped R, G, or B color channels based on the estimated chroma and the unclipped color channel(s) of the current pixel. The last step involves smoothing of the boundaries between regions of different clipping scenarios. Both objective and subjective experimental results show that our algorithm is very effective in restoring the color of clipped pixels.

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Index Terms:
Clipping, desaturation, color restoration, high dynamic range (HDR), inverse tone mapping.
Citation:
Di Xu, Colin Doutre, Panos Nasiopoulos, "Correction of Clipped Pixels in Color Images," IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 3, pp. 333-344, March 2011, doi:10.1109/TVCG.2010.63
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