rank_nrank_nRankNRankNrank_n (Operator)

Name

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

Signature

Description

The operator rank_nrank_nRankNRankNRankNrank_n 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 RankIndexRankIndexRankIndexRankIndexrankIndexrank_index is selected and placed in the output image at the same position. The output image has one channel.

In the special cases RankIndexRankIndexRankIndexRankIndexrankIndexrank_index = 1 and RankIndexRankIndexRankIndexRankIndexrankIndexrank_index = '(Number of channels)'"(Number of channels)""(Number of channels)""(Number of channels)""(Number of channels)""(Number of channels)" the minimum and maximum are returned. RankIndexRankIndexRankIndexRankIndexrankIndexrank_index = '(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""(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_nRankNRankNRankNrank_n should not be confused with the operator rank_imagerank_imageRankImageRankImageRankImagerank_image 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

compose2compose2Compose2Compose2Compose2compose2, compose3compose3Compose3Compose3Compose3compose3, compose4compose4Compose4Compose4Compose4compose4, compose5compose5Compose5Compose5Compose5compose5, add_channelsadd_channelsAddChannelsAddChannelsAddChannelsadd_channels

Alternatives

mean_nmean_nMeanNMeanNMeanNmean_n

See also

count_channelscount_channelsCountChannelsCountChannelsCountChannelscount_channels, rank_imagerank_imageRankImageRankImageRankImagerank_image

Module

Foundation