If all surrounding pixels are rejected, that segment is reconstructed using the “inpaint opposed” method (above). Pixels that are too dark or appear to be an edge are rejected by the algorithm. The color of each clipped segment is estimated by analysing the color ratios of the adjacent pixels. segmentation based A more sophisticated algorithm that uses adjacent unclipped pixels to estimate the correct color, by treating each clipped area separately (as an individual segment). This works well for the majority of images but may fail where the clipped areas are adjacent to areas of a different color. inpaint opposed (default) Restore clipped pixels by using an average of adjacent unclipped pixels to estimate the correct color. These methods all use unclipped channels and/or adjacent pixels to reconstruct the missing data. □highlight reconstruction methodsĪ number of highlight reconstruction methods are provided within this module. The crude method to resolve this is to clip the R and B channels to the clipping point of the G channel (the “clip highlights” reconstruction method), but this can result in the loss of valid pixel data that may be useful in highlight reconstruction, and may also cause other artefacts and hue shifts. For example, where only the G channel is clipped (and R and B are close to clipping) the white balance module can cause the R and B channels to be adjusted above the clipping point of the G channel leading to pink highlights that would otherwise have been white. These incorrect colors can then be further skewed by the white balance module, which adjusts the ratios of the R, G, and B channels to account for the overall color of the scene. If these pixels are left partially clipped it can result in unrealistic colors appearing in the image. The result will often be pixels (in the demosaiced image) that are clipped in some (R,G,B) channels but not others. When a camera captures light (using a normal Bayer sensor) each pixel represents a single color (R,G,B), which is then interpolated by the demosaic module to calculate the color of neighboring pixels. If the white point is set incorrectly for a given camera, this can lead to valid pixels being clipped and can adversely impact the effectiveness of this module. Darktable uses a camera’s “white point” to determine whether or not a given channel is clipped. Ideally, the photosite saturation point would be the same as the value at which digital clipping occurs (to make maximum use of the camera’s dynamic range) but these values often differ between cameras. Once a pixel is clipped we can no longer know the precise brightness of that pixel – only that it is equal to or greater than the maximum value that pixel can store. □clippingĬlipping occurs when the amount of captured light exceeds either the capacity of a camera’s sensor to record that light (photosite saturation) or the capacity of the Raw file to store it (digital clipping). Attempt to reconstruct color information for pixels that are clipped in one or more RGB channel.
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