Color Mathematical Morphology Based on Partial Ordering of Spectra

d’Ornellas, Marcos Cordeiro; Costa, José Augusto Fontoura

doi:10.1109/sibgrapi.2007.46

Cited by 6 publications

(1 citation statement)

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“…Angulo also proposed a method to use a reference color for computing color distance, where the distance-based and lexicographical approaches are generalized in RGB, LSH and Lab color spaces [3]. d'Ornellas and Costa proposed an ordering relation for colors that is based on the natural ordering of spectra [4]. As a result, they derived a color-model-independent approach for color mathematical morphology.…”

Section: Introductionmentioning

confidence: 99%

Order Space-Based Morphology for Color Image Processing

et al. 2023

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Mathematical morphology is a fundamental tool based on order statistics for image processing, such as noise reduction, image enhancement and feature extraction, and is well-established for binary and grayscale images, whose pixels can be sorted by their pixel values, i.e., each pixel has a single number. On the other hand, each pixel in a color image has three numbers corresponding to three color channels, e.g., red (R), green (G) and blue (B) channels in an RGB color image. Therefore, it is difficult to sort color pixels uniquely. In this paper, we propose a method for unifying the orders of pixels sorted in each color channel separately, where we consider that a pixel exists in a three-dimensional space called order space, and derive a single order by a monotonically nondecreasing function defined on the order space. We also fuzzify the proposed order space-based morphological operations, and demonstrate the effectiveness of the proposed method by comparing with a state-of-the-art method based on hypergraph theory. The proposed method treats three orders of pixels sorted in respective color channels equally. Therefore, the proposed method is consistent with the conventional morphological operations for binary and grayscale images.

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Section: Introductionmentioning

confidence: 99%