| Operators |
rank_rect — Compute a rank filter with rectangular masks.
rank_rect(Image : ImageRank : MaskWidth, MaskHeight, Rank : )
rank_rect performs a rank filter on the input image Image with a rectangular mask of size MaskWidth × MaskHeight and returns the filtered image in ImageRank.
Conceptually, the rank filter sorts all gray values within the mask in ascending order and then selects the gray value with rank Rank. The rank 1 corresponds to the smallest gray value and the rank MaskWidth * MaskHeight corresponds to the largest gray value within the mask. For Rank = (MaskWidth * MaskHeight - 1) / 2 + 1, rank_rect returns the median gray value (see median_rect). For Rank = 1, rank_rect performs a gray value erosion (see gray_erosion_rect, gray_erosion_shape, and gray_erosion), while for Rank = MaskWidth * MaskHeight rank_rect performs a gray value dilation (see gray_dilation_rect, gray_dilation_shape, and gray_dilation).
rank_rect can be used, for example, to suppress noise or to suppress unwanted objects that are smaller than the mask. Furthermore, rank_rect 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 MaskWidth * MaskHeight, slightly larger or smaller values should be selected for Rank.
If even values instead of odd values are passed in MaskHeight or MaskWidth, rank_rect uses the next larger odd values instead.
rank_rect uses an algorithm with constant runtime per pixel, i.e., the runtime only depends on the size of the input image and not on the mask size. Therefore, for large mask sizes rank_rect is the fastest implementation of the rank filter in HALCON. Depending on the computer architecture (processor type, availability of SIMD instructions like SSE2 or MMX, cache size and throughput, memory throughput), for small mask sizes the implementation used in rank_image is faster than rank_rect. Typically, this is the case for MaskHeight 15, but can also happen for larger mask sizes, e.g., if SIMD instructions are unavailable and memory throughput is low.
Furthermore, it should be noted that rank_rect 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_image is faster than rank_rect even for larger values of MaskHeight.
rank_rect should neither be used with Rank = 1 to perform a gray value erosion nor with Rank = MaskWidth * MaskHeight to perform a gray value dilation. In these cases, the operators gray_erosion_rect or gray_erosion_shape and gray_dilation_rect or gray_dilation_shape, respectively, are faster than rank_rect for almost all mask sizes.
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.
Image to be filtered.
Filtered image.
Width of the filter mask.
Default value: 15
Suggested values: 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 31, 49, 51, 61, 71, 81, 91, 101
Typical range of values: 3 ≤ MaskWidth ≤ 4095
Minimum increment: 2
Recommended increment: 2
Height of the filter mask.
Default value: 15
Suggested values: 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 31, 49, 51, 61, 71, 81, 91, 101
Typical range of values: 3 ≤ MaskHeight ≤ 4095
Minimum increment: 2
Recommended increment: 2
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
Minimum increment: 1
Recommended increment: 2
Restriction: 1 <= Rank && Rank <= MaskWidth * MaskHeight
For each pixel: O(1).
If the parameter values are correct the operator rank_rect returns the value 2 (H_MSG_TRUE). The behavior in case of empty input (no input images available) is set via set_system('no_object_result',<Result>). If necessary, an exception is raised.
threshold, dyn_threshold, regiongrowing
rank_image, median_rect, median_image
gray_erosion_rect, gray_dilation_rect, gray_erosion_shape, gray_dilation_shape, gray_erosion, gray_dilation
S. Perreault, P. Hébert; “Median Filtering in Constant Time”;
IEEE Transactions on Image Processing, vol. 16, no. 9,
pp. 2389-2394, 2007.
D. Cline, K.B. White, P.K. Egbert; “Fast 8-Bit Median Filtering
Based On Separability”; International Conference on Image
Processing, vol. V, pp. 281-284, 2007.
Foundation
| Operators |