Exposure vs Noise  - a comparison



 


At my last exposure workshop I explained  that the "best practical" exposure is with the cameras histogram data to the right as far as possible without any portion of the data actually touching the right hand side. The penalty for under exposure is noise, that setting the exposure to produce a histogram "to the right" and then adjusting the exposure slider in the RAW converter during conversion to TIF would produce an image with less noise than exposing the camera histogram for  a "hump in the middle". 

To illustrate the benefit of this approach I performed the following  test:

A Solid grey target approximating middle grey was taped to a wall and four consecutive photos were taken with an ISO setting of 3200 using a Canon 40D without noise reduction set. The first image  was with -1 ev compensation , i.e.  using the cameras metered setting and underexposing 1 ev. The next were at 0 (hump in the middle), +1  and +2 ev. The  image luminosity's were then normalized by converting to TIF with the RAW converter exposure compensations set at:  +1, 0,  -1, -2 respectively,  the idea being to produce four mid toned images of the same overall luminosity for comparison. The four TIF  images were then compared side by each, the original histogram representing the in camera exposure was added to each image for identification  purposes and the final image was converted to JPG for the web. 

It is clear from the comparison that exposing with the histogram "to the right" rather than for a "hump in the middle" produces a less noisy image.
 
 


Original RAW images shot at -1,  0, +1 and +2


 
 

After conversion to TIF with RAW exposure compensation applied


 
 
 

1- Raw conversions were performed with Breezebrowser Pro. ver 1.9.3, no noise reduction, 8 bit TIF.

2 - Overexposing slightly and correcting the exposure with the RAW converter will produce an even less noisy image - the problem is if the over exposure is excessive hi-light detail will be lost - but thats another story! 


 
 
 

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