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A New Quantification Method under Colorimetric Constraints

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In this work, we present a color quantification method based on the matrix of local pallets and colorimetric criteria. The proposed method extracts a set of onedimensional colors resulting from image partitioning. Image windowing depends upon the image variance, which gives information about color dispersion. The color sets are then used to generate the rows of the local pallet matrix that will be used as a smaller image but more interesting. The selection of the principal pallet used to quantify the color image is accomplished on the local pallet matrix by computing the histogram. From this histogram we extract recursively the most important color. Then, we eliminate its n most similar colors. To avoid conflict between equi-frequent colors we use EMD distance that determines the best color by matching the results. Finally, image is quantified by replacing each pixel's color by the nearest color from the final pallet.
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Document Type: Research Article

Publication date: January 1, 2002

More about this publication?
  • Started in 2002 and merged with the Color and Imaging Conference (CIC) in 2014, CGIV covered a wide range of topics related to colour and visual information, including color science, computational color, color in computer graphics, color reproduction, volor vision/psychophysics, color image quality, color image processing, and multispectral color science. Drawing papers from researchers, scientists, and engineers worldwide, DGIV offered attendees a unique experience to share with colleagues in industry and academic, and on national and international standards committees. Held every year in Europe, DGIV papers were more academic in their focus and had high student participation rates.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual papers for details.

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