Grass Valley KAM-XM-SERIES v.1.4.1 - Manual (Page 26)

26 KAM-XM-SERIES Instruction Manual
Configuration and Adjustments
Noise Reduction
Two of the modules covered in this manual (KAM-XM-UNC – Up Con-
verter with Noise Reduction and KAM-XM-UDC– Up/Down Converter)
provide the additional noise filtering and reduction controls described
below.
Spike Filtering
This is an adaptive median filter that works well in removing random
impulse noise. This type of filtering performs spatial processing to deter-
mine which pixels in an image have been affected by impulse noise. The
adaptive median filter classifies pixels as noise by comparing each pixel in
the image to its surrounding neighbor pixels. The size of the neighborhood
is adjustable, as well as the threshold for the comparison.
A pixel that is different from a majority of its neighbors, as well as being not
structurally aligned with those pixels to which it is similar, is labeled as
impulse noise. These noise pixels are then replaced by the median pixel
value of the pixels in the neighborhood that have passed the noise labeling
test. This results in a prime benefit of not eroding edges or other small
structures in the image with repeated application of the adaptive median
filter.
This type of filtering provides controls for setting the adaptive threshold of
the luminance and the chroma channels. The filter must be enabled to allow
processing.
Brickwall Filtering
This is a low pass filter with a sharp cutoff. This type of high-order low pass
filter attenuates high frequencies (image detail) while leaving low fre-
quency information unaffected. Impulse and Gaussian noise contain high
frequency components and will be diminished with this filter is on.
This filter is primarily intended for pre-compression processing, to atten-
uate high frequency information that will normally be quantized away in
the compression process. When used for pre-compression, it can improve
the efficiency and quality of the compression process. By controlling the
manner in which the detail is removed, compression artifacts can be mini-
mized. A boost can be applied after the brickwall filter to accentuate the
remaining edges in the filtered image.
One of the benefits of removing high frequency noise before compression
is that there are more bits to spend when generating the compressed stream
since there is less information to compress. In addition, the potential for
loss of desirable information due to the compression of small details is
decreased, resulting in a more consistent output.