Lightroom noise reduction revisited

A while ago, I wrote a post about noise reduction in Lightroom and how it compares to in-camera jpegs or capture NX (for Nikons) at very high ISOs. At that time, I concluded that Lightroom's noise reduction was weak. Over time however, I have come to appreciate the flipside of this coin. Both jpegs and capture NX conversions lose enormous amounts of detail because of the noise reduction applied. So much so that it can severely impact your image and make it look like it came from a point and shoot digital camera (i.e. terrible). To illustrate, here are some examples of this effect. I am employing the same rollover trick again as I have used before. Just roll your mouse over the titles and your browser will fetch that specific version. Be patient, depending on your connection, the first time this can take a few seconds to appear. After that, it will be instantaneous.


Capture NX default conversion
Lightroom default conversion
Capture NX with no noise reduction


And here is a different area.

Capture NX default conversion
Lightroom default conversion
Capture NX with no noise reduction


In my opinion, in both these examples, the default capture NX conversion pastes over lots of actual detail. I think the LR method actually gives a nice middle point between the images with noise reduction disabled in CNX and the ones with the default noise reduction. In the house image for example, the noise reduction completely gets rid of the structure in the fence, which is still visible in the Lightroom conversion. I do not like the appearance of the noise in Lightroom too much though. It seems to have a pasty character. Of course you should avoid looking this close too much at these superhigh ISO images. Of course a dedicated noise-reduction program will probably do a far better job than either. You can also see that although I used a camera-matching profile for the Lightroom conversions to give the same color as CNX, the yellow highlights on the house are not rendered as well in Lightroom as in CNX.