rank_nrank_nRankNRankN (Operator)

Name

rank_nrank_nRankNRankN — Return gray values with given rank from multiple channels.

Signature

Description

The operator rank_nrank_nRankNRankNRankN returns pixel-by-pixel the result of the rank-function over all channels.

For every pixel in the input image the following is being done: The gray values of all channels at this position are sorted in ascending order. Then the pixel with index RankIndexRankIndexRankIndexRankIndexrankIndex is selected and placed in the output image at the same position. The output image has one channel.

In the special cases RankIndexRankIndexRankIndexRankIndexrankIndex = 1 and RankIndexRankIndexRankIndexRankIndexrankIndex = '(Number of channels)'"(Number of channels)""(Number of channels)""(Number of channels)""(Number of channels)" the minimum and maximum are returned. RankIndexRankIndexRankIndexRankIndexrankIndex = '(Number of channels + 1) / 2'"(Number of channels + 1) / 2""(Number of channels + 1) / 2""(Number of channels + 1) / 2""(Number of channels + 1) / 2" returns the median (here, / denotes integer division). Hence, for a five-channel image, 3 returns the median.

The operator rank_nrank_nRankNRankNRankN should not be confused with the operator rank_imagerank_imageRankImageRankImageRankImage which computes the rank within a certain mask.

For an explanation of the concept of smoothing filters see the introduction of chapter Filters / Smoothing.

Attention

Note that filter operators may return unexpected results if an image with a reduced domain is used as input. Please refer to the chapter Filters.

Execution Information

• Multithreading type: reentrant (runs in parallel with non-exclusive operators).
• Multithreading scope: global (may be called from any thread).
• Automatically parallelized on tuple level.
• Automatically parallelized on domain level.

Parameters

Example (HDevelop)

compose5 (Image1, Image2, Image3, Image4, Image5, MultiChannelImage)
rank_n (MultiChannelImage, ImageMin, 1)
rank_n (MultiChannelImage, ImageMax, 5)
rank_n (MultiChannelImage, ImageMedian, 3)

Possible Predecessors

compose2compose2Compose2Compose2Compose2, compose3compose3Compose3Compose3Compose3, compose4compose4Compose4Compose4Compose4, compose5compose5Compose5Compose5Compose5, add_channelsadd_channelsAddChannelsAddChannelsAddChannels

Alternatives

mean_nmean_nMeanNMeanNMeanN

See also

count_channelscount_channelsCountChannelsCountChannelsCountChannels, rank_imagerank_imageRankImageRankImageRankImage

Module

Foundation