In this technique, a ray is generated for each desired image pixel.

The outlines of the detected object define the image area, the individual image pixels have to be replaced.

The image pixels do not contain the full specification of its color, but only its index in the palette.

But this creates a heavy dependence between the image pixels and its adaptive palette.

After forming the clusters, ground truth validation is done to identify the class the image pixel belongs to.

Combining this with the distance information, one can determine the position in three dimensions of the image pixel.

The features employed by the detection framework universally involve the sums of image pixels within rectangular areas.

All those sound channels and all those image pixels add up to a lot of data.

Generally this type of noise will only affect a small number of image pixels.

Multi-pass algorithms also exist, some of which run in linear time relative to the number of image pixels.