This is a slow and computationally-intensive method designed for maximum smoothness and seamless blending of the reconstructed regions into their neighborhood, and is designed primarily to reconstruct spotlights and specular reflections.

guided laplacians Use an algorithm (derived from the diffuse or sharpen module) to replicate details from valid channels into clipped channels and to propagate color gradients from valid surrounding regions into clipped regions.

Please note that this method can produce maze-like artifacts on highlights behind high-contrast edges, for example well-exposed fine structures in front of an overexposed background.

This method works very well on areas with homogeneous colors and is especially useful on skin tones with smoothly fading highlights. reconstruct color Use an algorithm that transfers color information from unclipped surroundings into the clipped highlights. As with clip highlights this method is a good option for naturally desaturated objects. This method works fairly well with a high-contrast base curve, which renders highlights desaturated. The reconstructed highlights will still be monochrome, but brighter and with more detail than with “clip highlights”. reconstruct in LCh Analyse each pixel with at least one clipped channel and attempt to correct the clipped pixel (in LCh color space) using the values of the other (3 for Bayer or 8 for X-Trans) pixels in the affected sensor block. This method is most useful in cases where clipped highlights occur in naturally desaturated objects (e.g. Three methods of reconstruction are available: clip highlights Clamp all pixels to the white level (i.e. For example pixels with both green and blue channels clipped will appear to be red without any highlight reconstruction. If these pixels are left partially clipped it can result in unrealistic colors appearing in the image. Attempt to reconstruct color information for pixels that are clipped in one or more RGB channel.

Recovering highlights using darktable