Abstract
Several color spaces defined in the literature are obtained from the RGB space through non-linear transforms, potentially limiting their applicability in a regularization context. Therefore, in this paper, we introduce three new color spaces, QTLC-\(r_*^2\), QTLC-\(g_*^2\), and QTLC-\(r_* g_*\), and the corresponding quadratic mappings from the RGB space. To test their uniformity, we use them to consider the image defading problem through a novel two-step technique: first, we define a fast heuristic to restore the natural color saturation; then, we propose a regularization technique to deblur the image. We experimentally observe that presumably thanks to its higher uniformity, the QTLC-\(r_* g_*\) space produces natural-looking images in the reconstruction and should be preferred to the QTLC-\(r_*^2\) and QTLC-\(g_*^2\) spaces.
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Biondi, G., Boccuto, A., Gerace, I. (2023). Quadratically Transformed Luminance Chrominance Spaces. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2023 Workshops. ICCSA 2023. Lecture Notes in Computer Science, vol 14108. Springer, Cham. https://doi.org/10.1007/978-3-031-37117-2_45
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