Authors:
Franklin César Flores
1
;
Leonardo Bespalhuk Facci
1
and
Roberto de Alencar Lotufo
2
Affiliations:
1
State University of Maringá, Brazil
;
2
State University of Campinas, Brazil
Keyword(s):
Color quantization, Morphological histogram processing, Watershed transform.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image Formation and Preprocessing
;
Image Quality
;
Mathematical Morphology
Abstract:
In a previous paper it was proposed a graylevel quantization method by morphological histogram processing. This paper introduces the extension of that quantization method to color images. Considering an image under the RGB color space model, this extension reduces the number of colors in the image by partitioning an 3-D histogram, similar to the RGB color space, in rectangular parallelepiped regions, through a iterative process. Such partitioning is done, in each iteration, by application of the graylevel quantization method to the longest dimension of the current region which has the greatest volume. The final classified color space is used to quantize the image. This paper also shows the comparison of the proposed method to the classical median cut one.