Who are the darktable users in 2020 ?

Study 22 min.
The core basics of design are to know for whom you design, that is who are the users of your solution, what they expect and what they need. It is also necessary to assess if the actual user of your product is the one you designed it for in the first place, that is, who is missing from your user base, to avoid the survivor bias . This is unfortunately overlooked in FLOSS and it is often not well regarded to collect user data.
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Interpolating (hue) angles

Study 9 min.
In image processing, retouchers may want to apply a saturation boost on specific hues only. Typically, uniform saturation corrections follow a basic linear transfer function $sat_{out} = gain \cdot sat_{in}$, where $gain$ is a real positive constant. To target specific hues, we simply rewrite $sat_{out}(hue) = gain(hue) \cdot sat_{in}$ where $gain$ is then a function. The most common way to declare $gain$ is to provide users with 8 discrete saturation nodes for 8 evenly-spaced hues, and interpolate smoothly between nodes.
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WebP is so great… except it's not

10 min.
I’m a responsible web designer, and as such, since WordPress (finally) accepts media uploads of image/webp MIME type and since all web browsers  newer than september 2020 (even Apple Safari \o/) can display it, I have been moving my photos library to WebP . After all, when you create content, the least you can do is to also provide the smoothest user experience around it. WebP falls close to magical: lookie those file weights !
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The sRGB book of color

1 min.
This page is inspired by the Munsell book of color. It aims at showing the sRGB gamut volume (all the visible colors that can be encoded as sRGB triplets), projected into a perceptually uniform lightness/chroma space (using JzAzBz color space1), and sliced across hue planes. The sRGB space is the lowest common denominator of all general-audience screens, and is deemed fit to choose colors for GUI, logos and drawings that should sit correctly on any display.
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Rotation-invariant Laplacian for 2D grids

14 min.
The Laplacian operator $\Delta u$ is the divergence of the gradient, that is the sum of the second-order partial derivatives $\nabla^2 u$ of a multivariate function, which represents the local curvature of this function. This operator is widely used for edge-detection1, as well as in partial-differential equations (Poisson, etc.), and other problems of machine-learning minimisation. For numerical applications in orthogonal graphs, sampled only at integer coordinates (like pixels in an image), a discrete Laplacian has to be used, and several approaches are available, that will be detailed hereafter.
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Derivating HDR-IPT direct and inverse transformations

53 min.
Following my work on the filmic tonemapping, several users have reported issues with very saturated blue areas (stage spotlights, bright skies) and red areas. The grail of image processing is being able to affect colors and brightness independantly. The big conundrum of tonemapping is raising luminance without affecting perceptual colors, and, by color, we mean hue and saturation/chroma. The problem is, once you lifted the luminance, you need to correct the saturation too, because it will look oversaturated.
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