Computational Colour Science Using MATLAB

By Stephen Westland, Caterina Ripamonti. 2004

320 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics

View Paper: https://www.semanticscholar.org/paper/40f0b978f932f3cce576be878a766aa478eae245

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atomic and Molecular Physics, and Optics

Citations in the corpus

pavo 2.0: new tools for the spectral and spatial analysis of colour in R (2018, methodology): “…visualised, as well as data from more specialised models, such as the colour hexagon (Chittka, 1992 ), CIEXYZ or LAB spaces (Smith & Guild, 1931 ; Westland et al. , 2012 ), categorical space (Troje, 1993 ), segment anal-114 ysis (Endler, 1990 ), the colour-opponent coding space (Backhaus, 1991…”
Using digital photography to study animal coloration (2007, methodology): “MATLAB has available an Image Processing Toolbox with a range of useful functions (Hanselman & Littlefield, 2001; Hunt et al ., 2003; Gonzalez, Woods & Eddins, 2004; Westland & Ripamonti, 2004).”
New Colors for Histology: Optimized Bivariate Color Maps Increase Perceptual Contrast in Histological Images (2015, methodology): “contrast) between two colors, we made use of the CIELAB color space (CIE International Commission on Illumination 1976 L a b ) [26, 27].”
O-HAZE: A Dehazing Benchmark with Real Hazy and Haze-Free Outdoor Images (2018, methodology): “Table 1 compares the output of different dehazing techniques with the ground-truth (haze free) images based on PSNR, SSIM [44] and CIEDE2000 [38, 45], for the images shown in Fig.”
Hyperspectral Imaging-Based Classification and Wavebands Selection for Internal Defect Detection of Pickling Cucumbers (2013, methodology): “…images were first transformed to the RGB images based on three illuminant spectra [i.e., blue skylight with correlated color temperature (CCT) 25,000 K, daylight with CCT 6,500 K, and evening sunlight with CCT 4,000 K] and the CIE 1931 color-matching functions (Westland and Ripamonti 2004).”
Camouflage through behavior in moths: the role of background matching and disruptive coloration (2015, methodology): “Then we transformed the camera’s red, green, and blue channel pixel values to a bird-specific color space (predicted photon catches for each cone cell type) using a polynomial mapping method (Párraga et al. 2002; Westland and Ripamonti 2004; Stevens et al. 2007, 2014) by a custom-built MATLAB progr”
Color change and camouflage in juvenile shore crabs Carcinus maenas (2014, methodology): “…(SWS), violet-sensitive (VS), and double cone (D) types by using a polynomial mapping technique to convert from camera to bird color space (see Westland and Ripamonti, 2004; Stevens et al., 2007a; Pike, 2011) using a custom written program in Image J, using a D65 standard irradiance spectrum.”