![]() ![]() A description of the Itcwb algorithim can be found here algorithm.Each movement of this command brings a new calculation of temperature, tint and correlation. You can use "Awb temperature bias" to adjust the results.A value of 1000 means either that calculation is not performed again and that the previous results are used, or that the algorithm has failed to compute a result in which case T=5002 is displayed.The GUI displays the correlation value:.If the shooting conditions are extreme (very low luminance values, etc.).Some DNG-type files obtained after conversion with a DNG or other converter."Underwater", "Fluorescent", "Led" lighting conditions may give bad results. If the illuminant does not have a CRI (Color Rendering Index) close to 100, e.g.This algorithm may give erroneous results:.The algorithm is based on the best correlation (Student's test) between the colors of the image and an array of 200 spectral reference colors. Provides a generally better color balance than auto “RGB grey". Works well for a wide range of scenes, and can be a good starting point for manual adjustments. This should generally give good results.Īutomatically corrects the white balance, by assuming that the average color of the scene is neutral gray. If you shoot only in raw (so no raw+JPG), put the white balance settings of your camera on auto. Takes the white balance used by the camera. This can be useful for diagnostic purposes or when working with UniWB images. When off, the multipliers are set to R=1 G=1 B=1 when working with raw files. The white balance tool can be turned on/off. Some people use this for creative effect, however there are various tools and operations which rely on the assumption that the white balance of the image is correct (for example highlight recovery in the Exposure tool, skin targeting in the Contrast by Detail Levels tool, sky targeting in the Wavelets tool, the CIECAM02 tool), so you should not misuse the white balance tool to create a color cast for artistic effect but rather use it to ensure that neutral areas remain neutral, and then use Color Toning or any of the other tools to render a creative color tint. Having an incorrect white balance results in the image having a color tint, typically warmer (orange) or colder (blue). Your perception of color changes depending on the color of the surroundings and of the illumination in your room, so don't always trust your eyes - verify using the method described above. You can do this even if you have a very miscalibrated monitor. You can tell whether the white balance of a spot which should be neutral is correct by checking whether that spot's RGB values match, or whether the a* and b* values in the L*a*b* color space match, or whether the RGB indicator bars under the main histogram are directly over each other. For example, R=G=B=65% and R=G=B=90% are both neutral, the former being darker than the latter. In order to make this operation more human-friendly, instead of operating on the three multipliers directly, the user is presented with an abstraction in the form of a temperature slider which adjusts colors along a blue-yellow axis, and a tint slider which adjusts them along the magenta-green axis.Ī neutral color is one whose red, green and blue values are equal. White balancing works by multiplying each of the primary colors by a different amount, until a satisfactory result is reached. Adjusting the white balance affects all colors, though it is easiest to discern whether the white balance is correct if an object you know to be of a neutral (white, gray) color looks non-neutral. One of these corrections is performed by adjusting the white balance - ensuring that neutral-colored (white) objects in the photographed scene still appear neutral on the photograph. For various reasons which you can read about in-depth elsewhere, the red, green and blue values which serve as the starting point in any raw photo development program need to be corrected in various ways before they resemble the photographed scene. 4.5.2 Data displayed in the GUI - limitations of interpretationĭigital images generally consist of a mixture of the three primary colors: red, green and blue.4.5 Simplified Temperature Correlation Algorithm.4 The Temperature Correlation Algorithm.
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