I generally have a tendency to underexpose images to avoid white clipping, especially when doing landscapes so that the sky doesn't get ruined as white clipping looks worse than black clipping. I know you can get use Lightroom tools to recover areas but I aim for the best shot when I'm taking it.

However I just read a book on Camera Raw ('Getting started with Camera Raw' by Ben Long - 2008) which explains you should lead towards overexposure rather than underexposure because the way cameras allocate bits towards capturing brightest is skewed towards the brightest part of the image. And therefore it has more data to play with when making adjustments in the brighter parts of the image than the darker.

Is this still true?

And why does it do this way rather proportionally the same for lights and darks? (The book didn't explain this).

  • Huh, never heard this before - I thought this attribute was only true of film.
    – icor103
    Oct 28, 2015 at 9:14
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    @mattdm: relative amount of photon shot noise decreases when the photon count increases.
    – Iliah Borg
    Oct 28, 2015 at 13:09
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    Overexposure is a wrong word here. Image is overexposed when the important details in the highlights are lost. The proper wording would be "maximize exposure", and the answer is "yes", for very obvious reasons. Technically, if the exposure is not maximized, the image is underexposed.
    – Iliah Borg
    Oct 28, 2015 at 13:30
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    When you "expose to the right" or purposefully overexpose you should avoid clipping the whites anyway where possible. I.e. when exposing to the right means clipping whites, you should not do it (unless you don't mind blowing out the white in a certain area).
    – DetlevCM
    Oct 28, 2015 at 15:08
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    Right okay yes right i shoudn't increase exposure if its mean highlight clipping but i should go for the maximum exposure I can which doesnt cause clipping even if that doesn't present the best looking image on the lcd as i take it, right ? Oct 28, 2015 at 16:11

2 Answers 2


For example, Nikon in compressed RAW cuts the number of bits for the highlights and leaves all the bits intacts for shadows.


The quantization discards information by converting 12 bits’ worth of data into into log2(683) = 9.4 bits’ worth of resolution. The dynamic range is unchanged. This is a fairly common technique – digital telephony encodes 12 bits’ worth of dynamic range in 8 bits using the so-called A-law and mu-law codecs. I modified the program to output the data for the decoding curve (Excel-compatible CSV format), and plotted the curve (PDF) using linear and log-log scales, along with a quadratic regression fit (courtesy of R). The curve resembles a gamma correction curve, linear for values up to 215, then quadratic.

In conclusion, Thom is right – there is some loss of data, mostly in the form of lowered resolution in the highlights.

Avoid clipping, that is important. The shadows have good details nowadays.

Also, if you have it, use Auto ADR (in Nikon cameras, check for other manufacturers). This automatically reduces exposure to avoid clipping and pushes (only in the JPEG) the shadows. If you use RAW, you get a darker image without clipping. No need to underexpose by an arbitrary amount, let the camera choose. With my D7100 it works perfectly. I used to use linear gamma to get a realistic histogram, but now no more.


There is a common misunderstanding with the technique described (which is generally dubbed 'expose to the right'), as far as I understand it.
You can find a detailed description at wikipedia, to see if the techniaues are the same:

However, the benefit of this techique mostly applies for images that are of lower contrast. If you have high contrast, it is always and without a doubt, lost information as soon as you clip highlights, while you will still get something from underexposed areas.

For landscape photography, the right way to tackle this problem however, would be graduated neutral density filters (or exposure bracketing). Here are two links for further input:
Ken Rockwell (hate him or hate him a bit):
bracketing vs. ND grads

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