More on Natural Masks

© Espion
Earlier I mentioned this topic.

I just like to add a few more ideas.

This is applicable for processing of landscape scenes particularly for sunsets.

At sunset the colour balance is rather complex. The shadows tend to be cold and the highlights, warm. (It is the same for sunrise too.)

And I exploit this fact with natural masks as follows.

I create a Multiply blending layer and masked it with the "natural" Blue mask (Ctrl-3).

(And the best way to create a blending layer, is to insert a Curves adjustment layer and change its blending mode to the one you desire.)

This does two things for the scene.

First it makes blue skies darker immediately. And secondly it adds more contrast to the hazy distance, and darkens the cold shadows.

I also create a Softlight blending layer and masked it with the "natural" Red mask (Ctrl-1).

This increases the contrasts in all the red component in the picture, such as the sunlight reflected off the clouds, and also increases the contrasts in the highlights, which has more red component.

But again there are downside and this is no magic formula - although I find it can do rather amazing things for some scenes (And for that I have created a Photoshop action for this series of blending and masking).

The downside is that it makes some parts of the pictures too dark and in some parts you lose contrasts.

This you can remedy with the help of a Screen layer. I hesitate to recommend a natural mask for Screen yet, for I have not found one that works all the time.

(Mostly I use the inverse of the natural Green or Luminosity mask, but this does not always work. More complex processing with Calculations may be required, or to adjust the shape of the curve in the Curves adjustment layer, if you have used a Curves adjustment layer as the blending layer.)

And then there is of course the noise.

As a fact of reality any processing to a picture increases its noise, but noise reduction software do a pretty good job to make it worth the "gains" from processing.

Photo credits: Lawrence Wee.

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