TY - JOUR
T1 - Dimensionality of color space in natural images
AU - BUADES, Antoni
AU - LISANI, Jose Luis
AU - MOREL, Jean-Michel
N1 - Research partially financed by the Centre National d’Etudes Spatiales (R&T), the European Research Council (advanced grants), and the Office of Naval Research (ONR; grant N00014-97-1-0839). The first two authors acknowledge partial support by the TIN2008-04752 project (Ministerio de Ciencia e Innovacion, Spain).
PY - 2011/2
Y1 - 2011/2
N2 - The color histogram [or color cloud) of a digital image displays the colors present in an image regardless of their spatial location and can be visualized in (R, G,B) coordinates. Therefore, it contains essential information about the structure of colors in natural scenes. The analysis and visual exploration of this structure is difficult. The color cloud being thick, its more dense points are hidden in the clutter. Thus, it is impossible to properly visualize the cloud density. This paper proposes a visualization method that also enables one to validate a general model for color clouds. It argues first by physical arguments that the color cloud must be essentially a two-dimensional (2D) manifold. A color cloud-filtering algorithm is proposed to reveal this 2D structure. A quantitative analysis shows that the reconstructed 2D manifold is strikingly close to the color cloud and only marginally depends on the filtering parameter. Thanks to this algorithm, it is finally possible to visualize the color cloud density as a gray-level function defined on the 2D manifold. © 2011 Optical Society of America.
AB - The color histogram [or color cloud) of a digital image displays the colors present in an image regardless of their spatial location and can be visualized in (R, G,B) coordinates. Therefore, it contains essential information about the structure of colors in natural scenes. The analysis and visual exploration of this structure is difficult. The color cloud being thick, its more dense points are hidden in the clutter. Thus, it is impossible to properly visualize the cloud density. This paper proposes a visualization method that also enables one to validate a general model for color clouds. It argues first by physical arguments that the color cloud must be essentially a two-dimensional (2D) manifold. A color cloud-filtering algorithm is proposed to reveal this 2D structure. A quantitative analysis shows that the reconstructed 2D manifold is strikingly close to the color cloud and only marginally depends on the filtering parameter. Thanks to this algorithm, it is finally possible to visualize the color cloud density as a gray-level function defined on the 2D manifold. © 2011 Optical Society of America.
UR - https://www.scopus.com/pages/publications/79751483424
U2 - 10.1364/JOSAA.28.000203
DO - 10.1364/JOSAA.28.000203
M3 - Journal Article (refereed)
AN - SCOPUS:79751483424
SN - 1084-7529
VL - 28
SP - 203
EP - 209
JO - Journal of the Optical Society of America A: Optics and Image Science, and Vision
JF - Journal of the Optical Society of America A: Optics and Image Science, and Vision
IS - 2
ER -