A two-sided but extremely biased comparison of noise reduction software
by Glenn Chan
The purpose of this article is to compare the pros and cons of Boundary Noise Reduction (BNR) compared to what I consider the leading competing products:
Please note that I may be extremely biased as my software competes against these other excellent noise removal tools!!!
With that being said, I will try to give a fair two-sided view on the noise reduction products on the market. Of course, you should try all the demos for the products yourself and make up your own mind!
For automatic profiling to work, the source image must have an area where there is no detail (i.e. the area is completely smooth) and only noise. This is not the case if there are no smooth areas in the picture to begin with. Automatic profiling can miss in such a situation, and you should manually tweak the noise reduction settings instead.
Another instance where automatic profiling tends to work poorly is if the camera applies its own noise reduction when recording to JPEG file formats. This can cause the profiling algorithm to get the characteristics of the remaining noise wrong.
For this and various other reasons, automatic profiling does not always work. There are some cases where the profiling is way off and manual intervention is needed to bring out the best results. Please keep that in mind since all the examples in this article are based on automatic settings.
All images are zoomed in 200%, nearest neighbour resizing. There is extreme noise in this random image of a newspaper sitting on a mall bench.
For Denoise, the best-looking preset was chosen. For all the others, automatic profiling was used. There was no manual tweaking of noise reduction parameters/settings.
Test image #2
This image of string contains a lot of fine detail and is a good demonstration of the ability to remove noise while removing as little detail as possible.
This situation is particularly favorable for Denoise as it can really extract a lot of detail while also getting rid of noise. Unfortunately, it also suffers from the worm-like artifacts as in the bench example (especially in the shadow areas). Manual intervention would be needed to remove these artifacts either by tweaking the filter settings or by using layer masks to remove them.
Noiseware does a good job but has problems dealing with noise outliers in the image.
Between Noise Ninja and Boundary Noise Reduction, the differences are mainly due to Noise Ninja using more aggressive profiling and sharpening.
Render times for a 10 megapixel image:
Noiseware and Noise Ninja are the fastest of the bunch, while Denoise is a magnitude slower than the rest.
*Please note that all times are approximate and vary depending on your system hardware, OS, other processes running, etc. etc. You should download the demos for each software and test for yourself.
Advantages of each product
If you have an image with extreme noise and need to "polish a turd" so to speak, Topaz Labs' Denoise is likely your best bet. It can recover detail that the other products cannot. For even better results, you can combine it with Boundary Noise Reduction as BNR tends to do a better job with chroma noise reduction. Duplicate the noisy image onto its own layer, apply BNR, and set the blending mode on the layer to "Color". This is the simplest method. You can also achieve similar results by setting "mix in original B&W detail" to 1 in BNR and apply BNR before Denoise.
For fastest processing times, consider Noiseware and Noise Ninja.
If you want conservative noise reduction with few artifacts, consider Boundary Noise Reduction.
But don't take my word for it! Please try the demos for each product yourself and come to your own conclusions. Each product tends to have its fans and all of them will do a good job at removing noise.
Other noise reduction products
This article does not cover other noise reduction software such as: