making the difference, for luminance only, between each pixel logarithm of the input image and the neighbouring pixels logarithm of the matching gaussian image.

To elaborate a 'Transmission Map' file obtained by Nevertheless, despite these handicaps, as we will see it further, results are more than satisfactory as well about processing time that in contrast and colors rendering, particularly by joining Retinex and Wavelets actions.įor more information, see the 'pdf' documents given in the 'Generalities' section.

But advantage, this process being situated before 'Denoise', the noise reduction will be here fully effective.

The fourth, sometimes, will need a white point modification, in order to avoid colors distortions (for example: a magenta sky).

The third consequence is the system response time which imposes to re-actualize the whole process after each change in the settings.

The second consequence of this position is that the characteristics of the raw data situated just after demosaicing are very different that the ones situated downstream: no gamma, no gamut limitation, no white balance, no RGB conversion… so we must expect artefacts and poor luminance and color rendering.

As a consequence, non raw files (TIFF, JPG, …) can't be processed with this algorithm? This problem should be solved soon (November 2015 ?).

The processing has been shifted from its dedicated place, that should have been close to 'Lab Adjustments' - near the beginning of the RawTherapee processing – that is necessarily (except if somebody has an idea to do differently) a raw process.

This limitation imposed by the gaussian function causes several consequences: The basic algorithm impose a reference to the whole image, and not to a crop or a reduction like in the RawTherapee processing. Wavelet_levels/fr#Avantages_.28.2B.29_et_inconv.C3.A9nients_.28-.29_de_Retinex.2Ffr_par_rapport_.C3.A0_Retinex_in_wavelet Imposed limitations by RawTherapee Quick comparison between the both versions ' Retinex in Wavelets' and ' Retinex at the beginning of the processing': Some of the quoted limitations are no more there ! I installed 2 possibilities to enable Retinex in the Wavelet process: Wavelet levels/fr.

It is the algorithm described in this page, with its limitations, advantages and drawbacks.

Retinex at the beginning of the processing where the user looks for special effects (tone mapping …).that are hazy, misty or having a veil of fog.The use of Retinex might be beneficial to images processing: and from some programming tricks inspired from '2003 Fabien Pelisson'.'Retinex Algorithm on Changing Scales for Haze Removal with Depth Map' (Weixing Wang, Lian Xu)'.'Automatic Image Haze Removal Based on Luminance Component' (Fan Guo, Zixing Cai, Bin Xie, Jin Tang'.Over the years many improvements have been added, but from my own point of view, no one is fully satisfactory. This said, this approach has no scientific basis and is only lying on experience and various empirical constants. The idea consists of characterizing the luminous information of a point from its intensity and the intensity of its neighbours.

This function and more particularly its general form is similar to a DOG (Difference Of Gaussian). In a way, this approach is pretty similar to CIECAM. The approach follows the human visual perception and the Edwin Land's retinal function. The first experimentation has been proposed by Rahman in 1996. Numerous theories and algorithms have been working out for more than 20 years. In addition to the digital photography, the Retinex algorithm (Retinex is the contraction for Retina + Cortex) is used in astronomy to show up information laying in the astronomical photographs, in medicine to detect not much visible structures in radiography and tomodensitometry. It is by copying the eyes biological mechanisms to adapt itself to these conditions that the MSR algorithm (MultiScale Retinex) has been created. While the eyes are able to see correctly the colors through a poor lighting, a colored surrounding or a veil of fog, cameras badly manage in theses conditions. 6.3 To boost the contrast and to reduce the atmospheric veil even more – Wavelet.

6.1.2 To apply a Gaussian mask and a gamma.

6.1.1 Transmission map adjustment – Iterations with Radius, contrast, scale.

6 A possible example – Dehaze – some recommendations.

5 Use in combination with wavelets and Lab Adjustments.

4.3 Practical synthesis of the various adjustments.

4.2 Adjustments accessible with 'Setting'.

3.6 Elaborating the 'Image Haze-free' file.

3.2 To process the mask resulting from the gaussian process.

3.1 To elaborate a 'Transmission Map' file obtained by.

1.1 Retinex at the beginning of the processing.

Preset filters in rawtherapee