Luminescence and Magnetic Properties of Two Three -Dimensional Terbium and Dysprosium MOFs Based on Azobenzene-4,4 '-Dicarboxylic Linker

We report the in situ formation of two novel metal-organic frameworks based on terbium and dysprosium ions using azobenzene-4,4-dicarboxylic acid (H(2)abd) as ligand, synthesized by soft hydrothermal routes. Both materials show isostructural three-dimensional networks with channels along a axis and display intense photoluminescence properties in the solid state at room temperature. Textural properties of the metal-organic frameworks (MOFs) have been fully characterized although no appreciable porosity was obtained. Magnetic properties of these materials were studied, highlighting the dysprosium material displays slightly frequency-dependent out of phase signals when measured under zero external field and under an applied field of 1000 Oe.

Linear Chromatic Adaptation Transform Based on Delaunay Triangulation

Computer vision algorithms that use color information require color constant images to operate correctly. Color constancy of the images is usually achieved in two steps: first the illuminant is detected and then image is transformed with the chromatic adaptation transform ( CAT). Existing CAT methods use a single transformation matrix for all the colors of the input image. The method proposed in this paper requires multiple corresponding color pairs between source and target illuminants given by patches of the Macbeth color checker. It uses Delaunay triangulation to divide the color gamut of the input image into small triangles. Each color of the input image is associated with the triangle containing the color point and transformed with a full linear model associated with the triangle. Full linear model is used because diagonal models are known to be inaccurate if channel color matching functions do not have narrow peaks. Objective evaluation showed that the proposed method outperforms existing CAT methods by more than 21%; that is, it performs statistically significantly better than other existing methods.

Linear Chromatic Adaptation Transform Based on Delaunay Triangulation

Computer vision algorithms that use color information require color constant images to operate correctly. Color constancy of the images is usually achieved in two steps: first the illuminant is detected and then image is transformed with the chromatic adaptation transform ( CAT). Existing CAT methods use a single transformation matrix for all the colors of the input image. The method proposed in this paper requires multiple corresponding color pairs between source and target illuminants given by patches of the Macbeth color checker. It uses Delaunay triangulation to divide the color gamut of the input image into small triangles. Each color of the input image is associated with the triangle containing the color point and transformed with a full linear model associated with the triangle. Full linear model is used because diagonal models are known to be inaccurate if channel color matching functions do not have narrow peaks. Objective evaluation showed that the proposed method outperforms existing CAT methods by more than 21%; that is, it performs statistically significantly better than other existing methods.