im.process_loc

\file \brief Image Processing - Local Operations

See Copyright Notice in im_lib.d

Members

Functions

imGaussianKernelSize2StdDev
float imGaussianKernelSize2StdDev(int kernel_size)

Calculates the standard deviation given the kernel size. * * \verbatim im.GaussianKernelSize2StdDev(kernel_size: number) -> stddev: number [in Lua 5] \endverbatim * \ingroup convolve

imGaussianStdDev2KernelSize
int imGaussianStdDev2KernelSize(float stddev)

Calculates the kernel size given the standard deviation. \n * If sdtdev is negative its magnitude will be used as the kernel size. * * \verbatim im.GaussianStdDev2KernelSize(stddev: number) -> kernel_size: number [in Lua 5] \endverbatim * \ingroup convolve

imProcessAddMargins
void imProcessAddMargins(const(imImage)* src_image, imImage* dst_image, int xmin, int ymin)

Increase the image size by adding pixels with zero value. \n * Images must be of the same type. Target image size must be greatter or equal than source image width+xmin, height+ymin. * * \verbatim im.ProcessAddMargins(src_image: imImage, dst_image: imImage, xmin: number, ymin: number) [in Lua 5] \endverbatim * \verbatim im.ProcessAddMarginsNew(image: imImage, xmin, xmax, ymin, ymax: number) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup resize

imProcessBarlettConvolve
int imProcessBarlettConvolve(const(imImage)* src_image, imImage* dst_image, int kernel_size)

Convolution with a barlett kernel. \n * Supports all data types. * * \verbatim im.ProcessBarlettConvolve(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessBarlettConvolveNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessBinMorphClose
int imProcessBinMorphClose(const(imImage)* src_image, imImage* dst_image, int kernel_size, int iter)

Dilate+Erode. * * \verbatim im.ProcessBinMorphClose(src_image: imImage, dst_image: imImage, kernel_size: number, iter: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessBinMorphCloseNew(image: imImage, kernel_size: number, iter: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup morphbin

imProcessBinMorphConvolve
int imProcessBinMorphConvolve(const(imImage)* src_image, imImage* dst_image, const(imImage)* kernel, int hit_white, int iter)

Base binary morphology convolution. \n * Images are all IM_BINARY. Kernel is IM_INT, but values can be only 1, 0 or -1. Use kernel size odd for better results. \n * Hit white means hit=1 and miss=0, or else hit=0 and miss=1. \n * Use -1 for don't care positions in kernel. Kernel values are simply compared with image values. \n * The operation can be repeated by a number of iterations. * The border is zero extended. \n * Almost all the binary morphology operations use this function.\n * If the kernel image attribute "Description" exists it is used by the counter. * * \verbatim im.ProcessBinMorphConvolve(src_image: imImage, dst_image: imImage, kernel: imImage, hit_white: boolean, iter: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessBinMorphConvolveNew(image: imImage, kernel: imImage, hit_white: boolean, iter: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup morphbin

imProcessBinMorphDilate
int imProcessBinMorphDilate(const(imImage)* src_image, imImage* dst_image, int kernel_size, int iter)

Binary morphology convolution with a kernel full of "0"s and hit black. * * \verbatim im.ProcessBinMorphDilate(src_image: imImage, dst_image: imImage, kernel_size: number, iter: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessBinMorphDilateNew(image: imImage, kernel_size: number, iter: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup morphbin

imProcessBinMorphErode
int imProcessBinMorphErode(const(imImage)* src_image, imImage* dst_image, int kernel_size, int iter)

Binary morphology convolution with a kernel full of "1"s and hit white. * * \verbatim im.ProcessBinMorphErode(src_image: imImage, dst_image: imImage, kernel_size: number, iter: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessBinMorphErodeNew(image: imImage, kernel_size: number, iter: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup morphbin

imProcessBinMorphOpen
int imProcessBinMorphOpen(const(imImage)* src_image, imImage* dst_image, int kernel_size, int iter)

Erode+Dilate. * When iteration is more than one it means Erode+Erode+Erode+...+Dilate+Dilate+Dilate+... * * \verbatim im.ProcessBinMorphOpen(src_image: imImage, dst_image: imImage, kernel_size: number, iter: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessBinMorphOpenNew(image: imImage, kernel_size: number, iter: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup morphbin

imProcessBinMorphOutline
int imProcessBinMorphOutline(const(imImage)* src_image, imImage* dst_image, int kernel_size, int iter)

Erode+Difference. \n * The difference from the source image is applied only once. * * \verbatim im.ProcessBinMorphOutline(src_image: imImage, dst_image: imImage, kernel_size: number, iter: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessBinMorphOutlineNew(image: imImage, kernel_size: number, iter: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup morphbin

imProcessBinMorphThin
void imProcessBinMorphThin(const(imImage)* src_image, imImage* dst_image)

Thins the supplied binary image using Rosenfeld's parallel thinning algorithm. \n * Reference: \n * "Efficient Binary Image Thinning using Neighborhood Maps" \n * by Joseph M. Cychosz, 3ksnn64@ecn.purdue.edu \n * in "Graphics Gems IV", Academic Press, 1994 \n * Not using OpenMP when enabled. * * \verbatim im.ProcessBinMorphThin(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim * \verbatim im.ProcessBinMorphThinNew(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup morphbin

imProcessCalcRotateSize
void imProcessCalcRotateSize(int width, int height, int* new_width, int* new_height, double cos0, double sin0)

Calculates the size of the new image after rotation. * * \verbatim im.ProcessCalcRotateSize(width: number, height: number, cos0: number, sin0: number) [in Lua 5] \endverbatim * \ingroup geom

imProcessCanny
void imProcessCanny(const(imImage)* src_image, imImage* dst_image, float stddev)

First part of the Canny edge detector. Includes the gaussian filtering and the nonmax suppression. \n * After using this you could apply a Hysteresis Threshold, see \ref imProcessHysteresisThreshold. \n * Image must be IM_BYTE/IM_GRAY. \n * Implementation from the book: \verbatim J. R. Parker "Algoritms for Image Processing and Computer Vision" WILEY \endverbatim * * \verbatim im.ProcessCanny(src_image: imImage, dst_image: imImage, stddev: number) [in Lua 5] \endverbatim * \verbatim im.ProcessCannyNew(image: imImage, stddev: number) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessCompassConvolve
int imProcessCompassConvolve(const(imImage)* src_image, imImage* dst_image, imImage* kernel)

Convolve with a kernel rotating it 8 times and getting the absolute maximum value. \n * Kernel must be square. \n * The rotation is implemented only for kernel sizes 3x3, 5x5 and 7x7. \n * Supports all data types except complex. * Returns zero if the counter aborted.\n * If the kernel image attribute "Description" exists it is used by the counter. * * \verbatim im.ProcessCompassConvolve(src_image: imImage, dst_image: imImage, kernel: imImage) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessCompassConvolveNew(image: imImage, kernel: imImage) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessConvolve
int imProcessConvolve(const(imImage)* src_image, imImage* dst_image, const(imImage)* kernel)

Base Convolution with a kernel. \n * Kernel can be IM_INT or IM_FLOAT, but always IM_GRAY. Use kernel size odd for better results. \n * Supports all data types. The border is mirrored. \n * Returns zero if the counter aborted. Most of the convolutions use this function.\n * If the kernel image attribute "Description" exists it is used by the counter. * * \verbatim im.ProcessConvolve(src_image: imImage, dst_image: imImage, kernel: imImage) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessConvolveNew(image: imImage, kernel: imImage) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessConvolveDual
int imProcessConvolveDual(const(imImage)* src_image, imImage* dst_image, const(imImage)* kernel1, const(imImage)* kernel2)

Base Convolution with two kernels. The result is the magnitude of the result of each convolution. \n * Kernel can be IM_INT or IM_FLOAT, but always IM_GRAY. Use kernel size odd for better results. \n * Supports all data types. The border is mirrored. \n * Returns zero if the counter aborted. Most of the convolutions use this function.\n * If the kernel image attribute "Description" exists it is used by the counter. * * \verbatim im.ProcessConvolveDual(src_image: imImage, dst_image: imImage, kernel1, kernel2: imImage) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessConvolveDualNew(image: imImage, kernel1, kernel2: imImage) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessConvolveRep
int imProcessConvolveRep(const(imImage)* src_image, imImage* dst_image, const(imImage)* kernel, int count)

Repeats the convolution a number of times. \n * Returns zero if the counter aborted.\n * If the kernel image attribute "Description" exists it is used by the counter. * * \verbatim im.ProcessConvolveRep(src_image: imImage, dst_image: imImage, kernel: imImage, count: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessConvolveRepNew(image: imImage, kernel: imImage, count: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessConvolveSep
int imProcessConvolveSep(const(imImage)* src_image, imImage* dst_image, const(imImage)* kernel)

Base convolution when the kernel is separable. Only the first line and the first column will be used. \n * Returns zero if the counter aborted.\n * If the kernel image attribute "Description" exists it is used by the counter. * * \verbatim im.ProcessConvolveSep(src_image: imImage, dst_image: imImage, kernel: imImage) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessConvolveSepNew(image: imImage, kernel: imImage) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessCrop
void imProcessCrop(const(imImage)* src_image, imImage* dst_image, int xmin, int ymin)

Extract a rectangular region from an image. \n * Images must be of the same type. Target image size must be smaller than source image width-xmin, height-ymin. \n * ymin and xmin must be >0 and <size. * * \verbatim im.ProcessCrop(src_image: imImage, dst_image: imImage, xmin: number, ymin: number) [in Lua 5] \endverbatim * \verbatim im.ProcessCropNew(image: imImage, xmin, xmax, ymin, ymax: number) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup resize

imProcessDiffOfGaussianConvolve
int imProcessDiffOfGaussianConvolve(const(imImage)* src_image, imImage* dst_image, float stddev1, float stddev2)

Difference(Gaussian1, Gaussian2). \n * Supports all data types, * but if source is IM_BYTE or IM_USHORT target image must be of type IM_INT. * * \verbatim im.ProcessDiffOfGaussianConvolve(src_image: imImage, dst_image: imImage, stddev1: number, stddev2: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessDiffOfGaussianConvolveNew(image: imImage, stddev1: number, stddev2: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessFlip
void imProcessFlip(const(imImage)* src_image, imImage* dst_image)

Apply a vertical flip. Swap lines. \n * Images must be of the same type and size. * Can be done in-place. * * \verbatim im.ProcessFlip(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim * \verbatim im.ProcessFlipNew(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup geom

imProcessGaussianConvolve
int imProcessGaussianConvolve(const(imImage)* src_image, imImage* dst_image, float stddev)

Convolution with a float gaussian kernel. \n * If sdtdev is negative its magnitude will be used as the kernel size. \n * Supports all data types. * * \verbatim im.ProcessGaussianConvolve(src_image: imImage, dst_image: imImage, stddev: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessGaussianConvolveNew(image: imImage, stddev: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessGrayMorphClose
int imProcessGrayMorphClose(const(imImage)* src_image, imImage* dst_image, int kernel_size)

Dilate+Erode. * * \verbatim im.ProcessGrayMorphClose(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessGrayMorphCloseNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup morphgray

imProcessGrayMorphConvolve
int imProcessGrayMorphConvolve(const(imImage)* src_image, imImage* dst_image, const(imImage)* kernel, int ismax)

Base gray morphology convolution. \n * Supports all data types except complex. Can be applied on color images. \n * Kernel is always IM_INT. Use kernel size odd for better results. \n * Use -1 for don't care positions in kernel. Kernel values are added to image values, then \n * you can use the maximum or the minimum within the kernel area. \n * No border extensions are used. * All the gray morphology operations use this function. \n * If the kernel image attribute "Description" exists it is used by the counter. * * \verbatim im.ProcessGrayMorphConvolve(src_image: imImage, dst_image: imImage, kernel: imImage, ismax: boolean) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessGrayMorphConvolveNew(image: imImage, kernel: imImage, ismax: boolean) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup morphgray

imProcessGrayMorphDilate
int imProcessGrayMorphDilate(const(imImage)* src_image, imImage* dst_image, int kernel_size)

Gray morphology convolution with a kernel full of "0"s and use maximum value. * * \verbatim im.ProcessGrayMorphDilate(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessGrayMorphDilateNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup morphgray

imProcessGrayMorphErode
int imProcessGrayMorphErode(const(imImage)* src_image, imImage* dst_image, int kernel_size)

Gray morphology convolution with a kernel full of "0"s and use minimum value. * * \verbatim im.ProcessGrayMorphErode(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessGrayMorphErodeNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup morphgray

imProcessGrayMorphGradient
int imProcessGrayMorphGradient(const(imImage)* src_image, imImage* dst_image, int kernel_size)

Difference(Erode, Dilate). * * \verbatim im.ProcessGrayMorphGradient(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessGrayMorphGradientNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup morphgray

imProcessGrayMorphOpen
int imProcessGrayMorphOpen(const(imImage)* src_image, imImage* dst_image, int kernel_size)

Erode+Dilate. * * \verbatim im.ProcessGrayMorphOpen(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessGrayMorphOpenNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup morphgray

imProcessGrayMorphTopHat
int imProcessGrayMorphTopHat(const(imImage)* src_image, imImage* dst_image, int kernel_size)

Open+Difference. * * \verbatim im.ProcessGrayMorphTopHat(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessGrayMorphTopHatNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup morphgray

imProcessGrayMorphWell
int imProcessGrayMorphWell(const(imImage)* src_image, imImage* dst_image, int kernel_size)

Close+Difference. * * \verbatim im.ProcessGrayMorphWell(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessGrayMorphWellNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup morphgray

imProcessInsert
void imProcessInsert(const(imImage)* src_image, const(imImage)* region_image, imImage* dst_image, int xmin, int ymin)

Insert a rectangular region in an image. \n * Images must be of the same type. Region image size can be larger than source image. \n * ymin and xmin must be >0 and <size. \n * Source and target must be of the same size. Can be done in-place. * * \verbatim im.ProcessInsert(src_image: imImage, region_image: imImage, dst_image: imImage, xmin: number, ymin: number) [in Lua 5] \endverbatim * \verbatim im.ProcessInsertNew(image: imImage, region_image: imImage, xmin: number, ymin: number) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup resize

imProcessInterlaceSplit
void imProcessInterlaceSplit(const(imImage)* src_image, imImage* dst_image1, imImage* dst_image2)

Split the image in two images, one containing the odd lines and other containing the even lines. \n * Images must be of the same type. Height of the output images must be half the height of the input image. * If the height of the input image is odd then the first image must have height equals to half+1. * * \verbatim im.ProcessInterlaceSplit(src_image: imImage, dst_image1: imImage, dst_image2: imImage) [in Lua 5] \endverbatim * \verbatim im.ProcessInterlaceSplitNew(image: imImage) -> new_image1: imImage, new_image2: imImage [in Lua 5] \endverbatim * \ingroup geom

imProcessLapOfGaussianConvolve
int imProcessLapOfGaussianConvolve(const(imImage)* src_image, imImage* dst_image, float stddev)

Convolution with a laplacian of a gaussian kernel. \n * Supports all data types, * but if source is IM_BYTE or IM_USHORT target image must be of type IM_INT. * * \verbatim im.ProcessLapOfGaussianConvolve(src_image: imImage, dst_image: imImage, stddev: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessLapOfGaussianConvolveNew(image: imImage, stddev: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessLocalMaxThreshold
int imProcessLocalMaxThreshold(const(imImage)* src_image, imImage* dst_image, int kernel_size, int min_level)

Threshold using a rank convolution with a local max function. \n * Returns zero if the counter aborted. \n * Supports all integer IM_GRAY images as source, and IM_BINARY as target. * * \verbatim im.ProcessLocalMaxThreshold(src_image: imImage, dst_image: imImage, kernel_size: number, min_level: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessLocalMaxThresholdNew(image: imImage, kernel_size: number, min_level: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup threshold

imProcessMeanConvolve
int imProcessMeanConvolve(const(imImage)* src_image, imImage* dst_image, int kernel_size)

Convolution with a kernel full of "1"s inside a circle. \n * Supports all data types. * * \verbatim im.ProcessMeanConvolve(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessMeanConvolveNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessMedianConvolve
int imProcessMedianConvolve(const(imImage)* src_image, imImage* dst_image, int kernel_size)

Rank convolution using the median value. \n * Returns zero if the counter aborted. \n * Supports all data types except complex. Can be applied on color images. * * \verbatim im.ProcessMedianConvolve(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessMedianConvolveNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup rank

imProcessMirror
void imProcessMirror(const(imImage)* src_image, imImage* dst_image)

Mirror the image in a horizontal flip. Swap columns. \n * Images must be of the same type and size. * Can be done in-place. * * \verbatim im.ProcessMirror(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim * \verbatim im.ProcessMirrorNew(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup geom

imProcessPrewittConvolve
int imProcessPrewittConvolve(const(imImage)* src_image, imImage* dst_image)

Magnitude of the prewitt convolution. \n * Supports all data types. * * \verbatim im.ProcessPrewittConvolve(src_image: imImage, dst_image: imImage) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessPrewittConvolveNew(image: imImage) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessRadial
int imProcessRadial(const(imImage)* src_image, imImage* dst_image, float k1, int order)

Apply a radial distortion using the given interpolation order (see imProcessResize). \n * Images must be of the same type and size. Returns zero if the counter aborted. * * \verbatim im.ProcessRadial(src_image: imImage, dst_image: imImage, k1: number, order: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessRadialNew(image: imImage, k1: number[, order]: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup geom

imProcessRangeContrastThreshold
int imProcessRangeContrastThreshold(const(imImage)* src_image, imImage* dst_image, int kernel_size, int min_range)

Threshold using a rank convolution with a range contrast function. \n * Supports all integer IM_GRAY images as source, and IM_BINARY as target. \n * Local variable threshold by the method of Bernsen. \n * Extracted from XITE, Copyright 1991, Blab, UiO \n * http://www.ifi.uio.no/~blab/Software/Xite/ \verbatim Reference: Bernsen, J: "Dynamic thresholding of grey-level images" Proc. of the 8th ICPR, Paris, Oct 1986, 1251-1255.

imProcessRangeConvolve
int imProcessRangeConvolve(const(imImage)* src_image, imImage* dst_image, int kernel_size)

Rank convolution using (maximum-minimum) value. \n * Returns zero if the counter aborted. \n * Supports all data types except complex. Can be applied on color images. * * \verbatim im.ProcessRangeConvolve(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessRangeConvolveNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup rank

imProcessRankClosestConvolve
int imProcessRankClosestConvolve(const(imImage)* src_image, imImage* dst_image, int kernel_size)

Rank convolution using the closest maximum or minimum value. \n * Returns zero if the counter aborted. \n * Supports all data types except complex. Can be applied on color images. * * \verbatim im.ProcessRankClosestConvolve(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessRankClosestConvolveNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup rank

imProcessRankMaxConvolve
int imProcessRankMaxConvolve(const(imImage)* src_image, imImage* dst_image, int kernel_size)

Rank convolution using the maximum value. \n * Returns zero if the counter aborted. \n * Supports all data types except complex. Can be applied on color images. * * \verbatim im.ProcessRankMaxConvolve(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessRankMaxConvolveNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup rank

imProcessRankMinConvolve
int imProcessRankMinConvolve(const(imImage)* src_image, imImage* dst_image, int kernel_size)

Rank convolution using the minimum value. \n * Returns zero if the counter aborted. \n * Supports all data types except complex. Can be applied on color images. * * \verbatim im.ProcessRankMinConvolve(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessRankMinConvolveNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup rank

imProcessReduce
int imProcessReduce(const(imImage)* src_image, imImage* dst_image, int order)

Only reduze the image size using the given decimation order. \n * Supported decimation orders: * \li 0 - zero order (mean) [default in Lua for MAP and BINARY] * \li 1 - first order (bilinear decimation) [default in Lua] * Images must be of the same type. If image type is IM_MAP or IM_BINARY, must use order=0. \n * Returns zero if the counter aborted. * * \verbatim im.ProcessReduce(src_image: imImage, dst_image: imImage, order: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessReduceNew(image: imImage, width, height[, order]: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup resize

imProcessReduceBy4
void imProcessReduceBy4(const(imImage)* src_image, imImage* dst_image)

Reduze the image area by 4 (w/2,h/2). \n * Images must be of the same type. Target image size must be source image width/2, height/2. * Can not operate on IM_MAP nor IM_BINARY images. * * \verbatim im.ProcessReduceBy4(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim * \verbatim im.ProcessReduceBy4New(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup resize

imProcessResize
int imProcessResize(const(imImage)* src_image, imImage* dst_image, int order)

Change the image size using the given interpolation order. \n * Supported interpolation orders: * \li 0 - zero order (near neighborhood) [default in Lua for MAP and BINARY] * \li 1 - first order (bilinear interpolation) [default in Lua] * \li 3 - third order (bicubic interpolation) * Images must be of the same type. If image type is IM_MAP or IM_BINARY, must use order=0. \n * Returns zero if the counter aborted. * * \verbatim im.ProcessResize(src_image: imImage, dst_image: imImage, order: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessResizeNew(image: imImage, width, height[, order]: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup resize

imProcessRotate
int imProcessRotate(const(imImage)* src_image, imImage* dst_image, double cos0, double sin0, int order)

Rotates the image using the given interpolation order (see \ref imProcessResize). \n * Images must be of the same type. The target size can be calculated using \ref imProcessCalcRotateSize to fit the new image size, * or can be any size, including the original size. The rotation is relative to the center of the image. \n * Returns zero if the counter aborted. * * \verbatim im.ProcessRotate(src_image: imImage, dst_image: imImage, cos0: number, sin0: number[, order]: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessRotateNew(image: imImage, cos0, sin0, order: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup geom

imProcessRotate180
void imProcessRotate180(const(imImage)* src_image, imImage* dst_image)

Rotates the image in 180 degrees. Swap columns and swap lines. \n * Images must be of the same type and size. * * \verbatim im.ProcessRotate180(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim * \verbatim im.ProcessRotate180New(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup geom

imProcessRotate90
void imProcessRotate90(const(imImage)* src_image, imImage* dst_image, int dir_clockwise)

Rotates the image in 90 degrees counterclockwise or clockwise. Swap columns by lines. \n * Images must be of the same type. Target width and height must be source height and width. \n * Direction can be clockwise (1) or counter clockwise (-1). * * \verbatim im.ProcessRotate90(src_image: imImage, dst_image: imImage, dir_clockwise: boolean) [in Lua 5] \endverbatim * \verbatim im.ProcessRotate90New(image: imImage, dir_clockwise: boolean) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup geom

imProcessRotateKernel
void imProcessRotateKernel(imImage* kernel)

Utility function to rotate a kernel one time. * * \verbatim im.ProcessRotateKernel(kernel: imImage) [in Lua 5] \endverbatim * \ingroup convolve

imProcessRotateRef
int imProcessRotateRef(const(imImage)* src_image, imImage* dst_image, double cos0, double sin0, int x, int y, int to_origin, int order)

Rotates the image using the given interpolation order (see \ref imProcessResize). \n * Images must be of the same type. Target can have any size, including the original size. \n * The rotation is relative to the reference point. But the result can be shifted to the origin. \n * Returns zero if the counter aborted. * * \verbatim im.ProcessRotateRef(src_image: imImage, dst_image: imImage, cos0: number, sin0: number, x: number, y: number, to_origin: boolean, order: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessRotateRefNew(image: imImage, cos0: number, sin0: number, x: number, y: number, to_origin: boolean[, order]: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup geom

imProcessSharp
int imProcessSharp(const(imImage)* src_image, imImage* dst_image, float amount, float threshold)

Edge enhancement using Laplacian8 mask. * amount controls how much the edges will enhance the image (0<amount<1), and * threshold controls which edges will be considered, it compares to twice of the absolute size of the edge. * * \verbatim im.ProcessSharp(src_image: imImage, dst_image: imImage, amount: number, threshold: number) [in Lua 5] \endverbatim * \verbatim im.ProcessSharpNew(image: imImage, amount: number, threshold: number) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessSharpKernel
int imProcessSharpKernel(const(imImage)* src_image, const(imImage)* kernel, imImage* dst_image, float amount, float threshold)

Edge enhancement using a given kernel. * If kernel has all positive values, then the unsharp technique is used, else sharp is used. * amount controls how much the edges will enhance the image (0<amount<1), and * threshold controls which edges will be considered, it compares to twice of the absolute size of the edge. * * \verbatim im.ProcessSharp(src_image: imImage, dst_image: imImage, amount: number, threshold: number) [in Lua 5] \endverbatim * \verbatim im.ProcessSharpNew(image: imImage, amount: number, threshold: number) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessSobelConvolve
int imProcessSobelConvolve(const(imImage)* src_image, imImage* dst_image)

Magnitude of the sobel convolution. \n * Supports all data types. * * \verbatim im.ProcessSobelConvolve(src_image: imImage, dst_image: imImage) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessSobelConvolveNew(image: imImage) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessSplineEdgeConvolve
int imProcessSplineEdgeConvolve(const(imImage)* src_image, imImage* dst_image)

Spline edge dectection. \n * Supports all data types. * * \verbatim im.ProcessSplineEdgeConvolve(src_image: imImage, dst_image: imImage) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessSplineEdgeConvolveNew(image: imImage) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessSwirl
int imProcessSwirl(const(imImage)* src_image, imImage* dst_image, float k1, int order)

Apply a swirl distortion using the given interpolation order (see imProcessResize). \n * Images must be of the same type and size. Returns zero if the counter aborted. * * \verbatim im.ProcessSwirl(src_image: imImage, dst_image: imImage, k: number, order: number) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessSwirlNew(image: imImage, k: number[, order]: number) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup geom

imProcessUnsharp
int imProcessUnsharp(const(imImage)* src_image, imImage* dst_image, float stddev, float amount, float threshold)

Edge enhancement using Unsharp mask. stddev control the gaussian filter, * amount controls how much the edges will enhance the image (0<amount<1), and * threshold controls which edges will be considered, it compares to twice of the absolute size of the edge. * Although very similar to \ref imProcessSharp, produces better results. * * \verbatim im.ProcessUnsharp(src_image: imImage, dst_image: imImage, stddev: number, amount: number, threshold: number) [in Lua 5] \endverbatim * \verbatim im.ProcessUnsharpNew(image: imImage, stddev: number, amount: number, threshold: number) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

imProcessZeroCrossing
void imProcessZeroCrossing(const(imImage)* src_image, imImage* dst_image)

Finds the zero crossings of IM_SHORT, IM_INT, IM_FLOAT and IM_DOUBLE images. Crossings are marked with non zero values * indicating the intensity of the edge. It is usually used after a second derivative, laplace. \n * Extracted from XITE, Copyright 1991, Blab, UiO \n * http://www.ifi.uio.no/~blab/Software/Xite/ * * \verbatim im.ProcessZeroCrossing(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim * \verbatim im.ProcessZeroCrossingNew(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve

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