rank_imagerank_imageRankImageRankImage (Operator)


rank_imagerank_imageRankImageRankImage — Compute a rank filter with arbitrary masks.


rank_image(Image, Mask : ImageRank : Rank, Margin : )

Herror rank_image(const Hobject Image, const Hobject Mask, Hobject* ImageRank, const Hlong Rank, const char* Margin)

Herror T_rank_image(const Hobject Image, const Hobject Mask, Hobject* ImageRank, const Htuple Rank, const Htuple Margin)

void RankImage(const HObject& Image, const HObject& Mask, HObject* ImageRank, const HTuple& Rank, const HTuple& Margin)

HImage HImage::RankImage(const HRegion& Mask, Hlong Rank, const HTuple& Margin) const

HImage HImage::RankImage(const HRegion& Mask, Hlong Rank, const HString& Margin) const

HImage HImage::RankImage(const HRegion& Mask, Hlong Rank, const char* Margin) const

HImage HImage::RankImage(const HRegion& Mask, Hlong Rank, const wchar_t* Margin) const   (Windows only)

static void HOperatorSet.RankImage(HObject image, HObject mask, out HObject imageRank, HTuple rank, HTuple margin)

HImage HImage.RankImage(HRegion mask, int rank, HTuple margin)

HImage HImage.RankImage(HRegion mask, int rank, string margin)


rank_imagerank_imageRankImageRankImageRankImage performs a rank filter on the input image ImageImageImageImageimage with a mask that is specified by the region MaskMaskMaskMaskmask and returns the filtered image in ImageRankImageRankImageRankImageRankimageRank. The shape of the mask can be chosen arbitrarily and can, for example, be created with operators like gen_circlegen_circleGenCircleGenCircleGenCircle or draw_regiondraw_regionDrawRegionDrawRegionDrawRegion. The position of the mask does not influence the result since the center of gravity of the mask region is used as the reference point of the mask.

Conceptually, the rank filter sorts all gray values within the mask in ascending order and then selects the gray value with rank RankRankRankRankrank. The rank 1 corresponds to the smallest gray value and the rank A corresponds to the largest gray value within the mask. Here, A denotes the area of MaskMaskMaskMaskmask (see area_centerarea_centerAreaCenterAreaCenterAreaCenter). For RankRankRankRankrank = (A - 1) / 2 + 1, rank_imagerank_imageRankImageRankImageRankImage returns the median gray value (see median_imagemedian_imageMedianImageMedianImageMedianImage). For RankRankRankRankrank = 1, rank_imagerank_imageRankImageRankImageRankImage performs a gray value erosion (see gray_erosion_rectgray_erosion_rectGrayErosionRectGrayErosionRectGrayErosionRect, gray_erosion_shapegray_erosion_shapeGrayErosionShapeGrayErosionShapeGrayErosionShape, and gray_erosiongray_erosionGrayErosionGrayErosionGrayErosion), while for RankRankRankRankrank = A rank_imagerank_imageRankImageRankImageRankImage performs a gray value dilation (see gray_dilation_rectgray_dilation_rectGrayDilationRectGrayDilationRectGrayDilationRect, gray_dilation_shapegray_dilation_shapeGrayDilationShapeGrayDilationShapeGrayDilationShape, and gray_dilationgray_dilationGrayDilationGrayDilationGrayDilation).

rank_imagerank_imageRankImageRankImageRankImage can be used, for example, to suppress noise or to suppress unwanted objects that are smaller than the mask. Furthermore, rank_imagerank_imageRankImageRankImageRankImage is less sensitive to noise than the correponding gray value morphology operators. Therefore, to obtain a more robust version of the gray value morphology, instead of using 1 or A, slightly larger or smaller values should be selected for RankRankRankRankrank.

Several border treatments can be chosen for filtering via the parameter MarginMarginMarginMarginmargin: gray value Pixels outside of the image borders are assumed to be constant (with the specified gray value). 'continued' Continuation of border pixels. 'cyclic' Cyclic continuation of image borders. 'mirrored' Reflection of pixels at the image borders.

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


rank_imagerank_imageRankImageRankImageRankImage uses an algorithm with a runtime per pixel that depends on the number of runs in the mask MaskMaskMaskMaskmask. Therefore, rank_imagerank_imageRankImageRankImageRankImage is slower than rank_rectrank_rectRankRectRankRectRankRect for rectangular masks with a large mask height. The precise mask height for which rank_rectrank_rectRankRectRankRectRankRect will become faster than rank_imagerank_imageRankImageRankImageRankImage depends on the computer architecture (processor type, availability of SIMD instructions like SSE2 or MMX, cache size and throughput, memory throughput). Typically, this is the case for mask heights > 15, but can also be the case only for larger mask sizes, e.g., if SIMD instructions are unavailable and memory throughput is low.

Furthermore, it should be noted that rank_rectrank_rectRankRectRankRectRankRect uses a recursive implementation, which internally computes the filter response on the smallest enclosing rectangle of the domain of the input image. Therefore, if the domain of the input image only covers a small fraction of the smallest enclosing rectangle, it can happen that rank_imagerank_imageRankImageRankImageRankImage is faster than rank_rectrank_rectRankRectRankRectRankRect even for larger mask heights.

rank_imagerank_imageRankImageRankImageRankImage should neither be used with RankRankRankRankrank = 1 to perform a gray value erosion nor with RankRankRankRankrank = A to perform a gray value dilation. In these cases, the operators gray_erosion_rectgray_erosion_rectGrayErosionRectGrayErosionRectGrayErosionRect, gray_erosion_shapegray_erosion_shapeGrayErosionShapeGrayErosionShapeGrayErosionShape, or gray_erosiongray_erosionGrayErosionGrayErosionGrayErosion and gray_dilation_rectgray_dilation_rectGrayDilationRectGrayDilationRectGrayDilationRect, gray_dilation_shapegray_dilation_shapeGrayDilationShapeGrayDilationShapeGrayDilationShape, or gray_dilationgray_dilationGrayDilationGrayDilationGrayDilation, respectively, are typically faster than rank_imagerank_imageRankImageRankImageRankImage.

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


ImageImageImageImageimage (input_object)  (multichannel-)image(-array) objectHImageHImageHobject (byte / int2 / uint2 / int4 / real)

Image to be filtered.

MaskMaskMaskMaskmask (input_object)  region objectHRegionHRegionHobject

Filter mask.

ImageRankImageRankImageRankImageRankimageRank (output_object)  multichannel-image(-array) objectHImageHImageHobject * (byte / int2 / uint2 / int4 / real)

Filtered image.

RankRankRankRankrank (input_control)  integer HTupleHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Rank of the output gray value.

Default value: 5

Suggested values: 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 31, 49, 51, 61, 71, 81, 91, 101

Typical range of values: 1 ≤ Rank Rank Rank Rank rank ≤ 4095

Minimum increment: 1

Recommended increment: 2

MarginMarginMarginMarginmargin (input_control)  string HTupleHTupleHtuple (string / integer / real) (string / int / long / double) (HString / Hlong / double) (char* / Hlong / double)

Border treatment.

Default value: 'mirrored' "mirrored" "mirrored" "mirrored" "mirrored"

Suggested values: 'mirrored'"mirrored""mirrored""mirrored""mirrored", 'cyclic'"cyclic""cyclic""cyclic""cyclic", 'continued'"continued""continued""continued""continued", 0, 30, 60, 90, 120, 150, 180, 210, 240, 255

Example (HDevelop)

read_image (Image, 'fabrik')
draw_region (Region, WindowHandle)
rank_image (Image, Region, ImageRank, 5, 'mirrored')


For each pixel: O(N), where N is the number of runs of MaskMaskMaskMaskmask (see runlength_featuresrunlength_featuresRunlengthFeaturesRunlengthFeaturesRunlengthFeatures).


If the parameter values are correct the operator rank_imagerank_imageRankImageRankImageRankImage returns the value 2 (H_MSG_TRUE). The behavior in case of empty input (no input images available) is set via the operator set_system('no_object_result',<Result>)set_system("no_object_result",<Result>)SetSystem("no_object_result",<Result>)SetSystem("no_object_result",<Result>)SetSystem("no_object_result",<Result>). If necessary, an exception is raised.

Possible Predecessors

read_imageread_imageReadImageReadImageReadImage, draw_regiondraw_regionDrawRegionDrawRegionDrawRegion, gen_circlegen_circleGenCircleGenCircleGenCircle, gen_rectangle1gen_rectangle1GenRectangle1GenRectangle1GenRectangle1, gen_rectangle2gen_rectangle2GenRectangle2GenRectangle2GenRectangle2

Possible Successors

thresholdthresholdThresholdThresholdThreshold, dyn_thresholddyn_thresholdDynThresholdDynThresholdDynThreshold, regiongrowingregiongrowingRegiongrowingRegiongrowingRegiongrowing


rank_rectrank_rectRankRectRankRectRankRect, median_imagemedian_imageMedianImageMedianImageMedianImage, median_rectmedian_rectMedianRectMedianRectMedianRect

See also

gray_erosion_rectgray_erosion_rectGrayErosionRectGrayErosionRectGrayErosionRect, gray_dilation_rectgray_dilation_rectGrayDilationRectGrayDilationRectGrayDilationRect, gray_erosion_shapegray_erosion_shapeGrayErosionShapeGrayErosionShapeGrayErosionShape, gray_dilation_shapegray_dilation_shapeGrayDilationShapeGrayDilationShapeGrayDilationShape, gray_erosiongray_erosionGrayErosionGrayErosionGrayErosion, gray_dilationgray_dilationGrayDilationGrayDilationGrayDilation


T.S. Huang, G.J. Yang, G.Y. Tang; “A Fast Two-Dimensional Median Filtering Algorithm”; IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 27, no. 1, pp. 13-18, 1979.
R. Haralick, L. Shapiro; “Computer and Robot Vision”; Addison-Wesley, 1992, pp. 318-320.