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Project:	Dr. Dmitriy Vatolin
Implementation, ideas:	Konstantin Strelnikov Maxim Makhinya

We developed new methods of removing and applying of the film grain (specific type of noise that is usually present in materials that were captured from film). Our methods allow extraction of film grain information from video and using it for applying of the grain that is very similar to original.
Some examples and explanation you can find below.

Results

Here are three examples of film grain from real video, it could be easily seen that film grain has another structure than digital noise. In most cases film grain makes video more natural and also masks some small artifacts:

Frame from DA sequence (720x353 94KB)

Frame from MI sequence (640x272 70KB)

Frame from DTs sequence (1920x1088 640KB)

We have developed several methods for film grain removal including temporal and spatial noise filtration; you can find few examples below:

Source fragment from DA	Grain removal results
Source fragment from MI	Grain removal results
Source fragment from DTs	Grain removal results

We are proposing two types of grain parameters estimation:

• Noise parameters estimation
• Finding the best matching pattern in the predefined database

Source fragment from DA	Regraining results
Source fragment from MI	Regraining results

We have obtained these results by original video de-graining, determining grain parameters and applying grain to the de-grained video. Structures of grain in the regrained frames look very similar to the original sources.

The following example shows how regraining technique helps to increase quality and makes compression artifacts significantly less noticeable:

Source fragment from DA

Regraining results

These methods provides possibility to add grain to any other video, making it more natural (for example adding grain to synthetic video). This also makes compressed video look better especially in case when original grain was corrupted by lossy video encoder.

Download

Please contact us if you are interested in a commercial license.

Other resources

Video resources:

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Last updated: 12-October-2007

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Project sponsored by YUVsoft Corp.

Project supported by MSU Graphics & Media Lab