The biops Package. August 14, 2007

Transcription

1 The biops Package August 14, 2007 Type Package Title Basic image operations and image processing Version Date Author Matias Bordese, Walter Alini Maintainer Matias Bordese Encoding UTF-8 This package includes arithmetic, logic, look up table and geometric operations. Some image processing functions, for edge detection (several algorithms including roberts, sobel, kirsch, marr-hildreth, canny) and operations by convolution masks (with predefined as well as user defined masks) are provided. Supported file formats are jpeg and tiff (it requires libtiff and libjpeg libraries installed). SystemRequirements libtiff, libjpeg License GPL R topics documented: biops-package imagetype imagedata imgand imgadd imgaverage imgaverageshrink imgbilinearrotate imgbilinearscale imgblueband imgblur imgboost

2 2 R topics documented: imgcanny imgconvolve imgcrop imgcubicrotate imgcubicscale imgdecreasecontrast imgdecreaseintensity imgdiffer imgdifferenceedgedetection imgdivide imgfreichen imggamma imggetrgbfrombands imggreenband imghighpassfilter imghistogram imghomogeneityedgedetection imghorizontalmirroring imgincreasecontrast imgincreaseintensity imgkirsch imgmarrhildreth imgmaximum imgmedianshrink imgmultiply imgnearestneighborrotate imgnearestneighborscale imgnegative imgnormalize imgor imgprewitt imgprewittcompassgradient imgrgb2grey imgredband imgroberts imgrobinson3level imgrobinson5level imgrotate imgrotate90clockwise imgrotate90counterclockwise imgscale imgsharpen imgshencastan imgsobel imgsplinerotate imgsplinescale imgstdblur imgthreshold

3 biops-package 3 imgtranslate imgunsharpen imgverticalmirroring imgxor logo plot.imagedata print.imagedata r_dec_contrast r_dec_intensity r_gamma r_imgadd r_imgaverage r_imgdiffer r_imgmaximum r_inc_contrast r_inc_intensity r_look_up_table r_negative r_negative_lut r_threshold readjpeg readtiff writejpeg writetiff Index 67 biops-package Basic image operations Details Basic image operations. It includes: arithmetic, logic, look up table and geometric operations. The supported file formats are jpeg and tiff. Package: biops Type: Package Version: 0.1 Date: License: GPL Built: R 2.2.1; i486-pc-linux-gnu; :02:45; unix Index: biops-package Basic image operations

4 4 biops-package imagetype imagedata imgand imgadd imgaverage imgaverageshrink imgbilinearrotate imgbilinearscale imgblueband imgcubicrotate imgcubicscale imgdecreasecontrast imgdecreaseintensity imgdiffer imgdivide imggamma imggreenband imghorizontalmirroring Get information on color type of imagedata Generate an imagedata And two images Add two images Average images Shrink an image Rotate an image Scale an image Return the image blue band Rotate an image Scale an image Decrease contrast Decrease intensity Substract two images Divide two images Gamma correct an image Return the image green band Horizontal mirror an image Increase contrast Increase intensity Shrink an image Multiply two images imgincreasecontrast imgincreaseintensity imgmedianshrink imgmultiply imgnearestneighborrotate Rotate an image imgnearestneighborscale Scale an image imgnegative Negate an image imgnormalize Normalization for vector and matrix imgor Or two images imgrgb2grey Convert color imagedata to grey imagedata imgredband Return the image red band imgrotate Rotate an image imgrotate90clockwise Rotate an image imgrotate90counterclockwise Rotate an image imgscale Scale an image imgsplinerotate Rotate an image imgsplinescale Scale an image imgthreshold Threshold an image imgtranslate Translate an image block imgverticalmirroring Vertical mirror an image imgxor Xor two images logo R logo imagedata plot.imagedata Plotting an imagedata object print.imagedata Print information on a given imagedata object r_dec_contrast Decrease contrast r_dec_intensity Decrease intensity

5 imagetype 5 r_gamma_img r_imgadd r_imgaverage r_imgdiffer r_inc_contrast r_inc_intensity r_negative r_threshold readjpeg readtiff violet.picture writejpeg writetiff Gamma correct an image Add two images Average images Substract two images Increase contrast Increase intensity Negate an image Threshold an image Read jpeg file Read tiff file JPEG picture of a violet flower Write jpeg file Write tiff file Author(s) Matà as Bordese, Walter Alini Maintainer: Matà as Bordese <mbordese@yahoo.com> imagetype Get information on color type of imagedata This function returns color type ("rgb" or "grey") of a given imagedata. imagetype(x) x "rgb" or "grey" cat("image Type", imagetype(x))

6 6 imagedata imagedata Generate an imagedata This function makes an imagedata object from a matrix. This data structure is primary data structure to represent image in biops package. imagedata(mat, type=null, ncol=dim(mat)[1], nrow=dim(mat)[2]) mat type ncol nrow array, matrix or vector "rgb" or "grey" width of image height of image Details For grey scale image, matrix should be given in the form of 2 dimensional matrix. First dimension is row, and second dimension is column. For rgb image, matrix should be given in the form of 3 dimensional array (row, column, channel). mat[ 1], mat[ 2], mat[ 3] are red plane, green plane and blue plane, respectively. You can omit type specification if you give a proper array or matrix. plot.imagedata print.imagedata p <- q <- seq(-1, 1, length=20) r <- 1 - outer(p^2, q^2, "+") / 2 plot(imagedata(r))

7 imgand 7 imgand And two images This function does a logic AND between two images and returns a new image. imgand(1, 2) 1 2 The first image The second image imgor imgxor y <- imgand(x, x) imgadd Add two images This function adds two images and returns a new image. imgadd(1, 2) 1 2 The first image The second image

8 8 imgaverage Note To add a constant c to an image you can just do:»> + c. y <- imgadd(x, x) imgaverage Average images This function calculates the average of the given images and returns a new image. imgaverage(_list) _list An image list y <- imgaverage(list(x, x))

9 imgaverageshrink 9 imgaverageshrink Shrink an image This function shrinks an image using the average and returns a new image. imgaverageshrink(, x_scale, y_scale) x_scale y_scale The horizontal scale factor The vertical scale factor Note The scale factors are expected to be less than 1. imgmedianshrink imgnearestneighborscale imgbilinearscale imgcubicscale y <- imgaverageshrink(x, 0.5, 0.5)

10 10 imgbilinearscale imgbilinearrotate Rotate an image This function rotates an image using bilinear interpolation and returns a new image. imgbilinearrotate(, angle) angle The clockwise deg angle to rotate imgrotate imgnearestneighborrotate imgcubicrotate imgsplinerotate imgrotate90clockwise imgrotate90counterclockwise y <- imgbilinearrotate(x, 45) imgbilinearscale Scale an image This function scales an image using bilinear interpolation and returns a new image. imgbilinearscale(, x_scale, y_scale)

11 imgblueband 11 x_scale y_scale The horizontal scale factor The vertical scale factor Note The scale factors are expected to be greater than 1. To reduce an image use the minification functions instead. imgscale imgnearestneighborscale imgcubicscale imgsplinescale imgmedianshrink imgaverageshrink y <- imgbilinearscale(x, 1.5, 1.5) imgblueband Return the image blue band This function returns the blue band of the imagedata. imgblueband(x) x grey imagedata

12 12 imgblur plot(imgblueband(x)) imgblur Blurs an image This function blurs an image by convoluting with the following matrix: 1/16 1/8 1/16 1/8 1/4 1/8 1/16 1/8 1/16 imgblur() imgstdblur y <- imgstdblur(x)

13 imgboost 13 imgboost High Boosts an image This function high boosts an image by convoluting with the following matrix:

14 14 imgcanny -1/9-1/9-1/9-1/9 (9p-1)/9-1/9-1/9-1/9-1/9 It increases intensity by a given proportion (p) and substracting a lowpass filter imgboost(, proportion) proportion Proportion of intensity to be increased (optional: default = 1 -HighPassFilter-) Note When proportion=1, it s the same as imghighpassfilter y <- imgboost(x, 1.2) imgcanny Canny Edge Detection Method This function does edge detection using the Canny algorithm. imgcanny(, sigma, low=0, high=-1) sigma low high The standard deviation used for the gaussian smoothing convolution The lower threshold for hysteresis The higher threshold for hysteresis

15 imgconvolve 15 Note If not specified, the low and high parameters are estimated based in a histogram of the image. y <- imgcanny(x, 0.7) imgconvolve Performs an image convolution This function performs an image convolution with given mask imgconvolve(, mask, bias) mask bias Kernel s convolution matrix to be added to each pixel after method is applied (used to correct some expected behaviour). This argument is optional (default = 32) m <- matrix(c(1,2,1,2,4,2,1,2,1)/16, 3, 3, byrow = TRUE) y <- imgconvolve(x, m, 64)

16 16 imgcubicrotate imgcrop Crops an image This function crops image. imgcrop(, x_start, y_start, c_width, c_height) x_start y_start c_width c_height Upper left x coordinate of source block Upper left y coordinate of source block Width of the block to crop Height of the block to crop y <- imgcrop(x, 100, 50, 100, 50) imgcubicrotate Rotate an image This function rotates an image using cubic interpolation and returns a new image. imgcubicrotate(, angle) angle The clockwise deg angle to rotate

17 imgcubicscale 17 imgrotate imgnearestneighborrotate imgbilinearrotate imgsplinerotate imgrotate90clockwise imgrotate90counterclockwise y <- imgcubicrotate(x, 45) imgcubicscale Scale an image This function scales an image using cubic interpolation and returns a new image. imgcubicscale(, x_scale, y_scale) x_scale y_scale The horizontal scale factor The vertical scale factor Note The scale factors are expected to be greater than 1. To reduce an image use the minification functions instead. imgscale imgnearestneighborscale imgbilinearscale imgsplinescale imgmedianshrink imgaverageshrink

18 18 imgdecreasecontrast y <- imgcubicscale(x, 1.5, 1.5) imgdecreasecontrast Decrease contrast This function decreases an image contrast, leaving each pixel value between given values. imgdecreasecontrast(, min_desired, max_desired) min_desired max_desired The min value The max value imgincreasecontrast r_dec_contrast r_inc_contrast y <- imgdecreasecontrast(x, 60, 200)

19 imgdecreaseintensity 19 imgdecreaseintensity Decrease intensity This function decreases an image intensity by a given factor. imgdecreaseintensity(, percentage) percentage A non negative value representing the intensity percentage to be decreased. 1 stands for 100% (eg. 0.5 = 50%). imgincreaseintensity r_dec_intensity r_inc_intensity y <- imgdecreaseintensity(x, 0.3) imgdiffer Substract two images This function substracts two images and returns a new image, 1-2. imgdiffer(1, 2)

20 20 imgdifferenceedgedetection 1 2 The first image The second image Note To substract a constant c to an image you can just do:»> - c. y <- imgdiffer(x, x) imgdifferenceedgedetection Enhaces image edges This function enhaces image s edge by the difference method. It uses a 3x3 matrix to determine the current pixel value (by getting the maximum value between the distances of matrix s opposite neighbors imgdifferenceedgedetection(, bias) bias to be added to each pixel after method is applied (used to correct some expected behaviour). This argument is optional (default = 32) imghomogeneityedgedetection

21 imgdivide 21 y <- imgdifferenceedgedetection(x, bias=64) imgdivide Divide two images This function divides two images and returns a new image. imgdivide(1, 2) 1 2 The first image The second image Note To divide an image by a constant c you can just do:»> / c. y <- imgdivide(x, x) imgfreichen Frei-Chen Edge Detection Method This function enhaces image s edges by convoluting with the Frei-Chen method matrices:

22 22 imggamma H_r H_c imgfreichen() y <- imgfreichen(x) imggamma Gamma correct an image This function applies gamma operation to a given image. Each pixel value is taken to the inverse of gamma_value-th exponent. imggamma(, gamma_value) gamma_value A non negative value representing operation gamma value r_gamma

23 imggetrgbfrombands 23 y <- imggamma(x, 1.3) imggetrgbfrombands Return an RGB image This function returns the RGB image compositing the given bands. imggetrgbfrombands(r, G, B) R G B A one-band image for the Red band A one-band image for the Green band A one-band image for the Blue band RGB imagedata r <- imgredband(x) g <- imggreenband(x) b <- imgblueband(x) rgb <- imggetrgbfrombands(r, g, b)

24 24 imghighpassfilter imggreenband Return the image green band This function returns the green band of the imagedata. imggreenband(x) x grey imagedata plot(imggreenband(x)) imghighpassfilter Sharpens an image This function sharpens an image by convoluting with the following matrix: -1/9-1/9-1/9-1/9 8/9-1/9-1/9-1/9-1/9 imghighpassfilter ()

25 imghistogram 25 y <- imghighpassfilter(x) imghistogram Return the image histogram This function returns the image pixel values histogram. imghistogram(x, main='image Histogram', col='midnight Blue',...) x main The histogram title col The histogram bars color... Same options of hist function histogram object hist h <- imghistogram(x)

26 26 imghorizontalmirroring imghomogeneityedgedetection Enhaces image edges This funtions enhaces image s edge by the homogeneity method. It uses a 3x3 matrix to determine the current pixel value (by getting the maximum value between the distances of the pixel and its neighbors) imghomogeneityedgedetection(, bias) bias to be added to each pixel after method is applied (used to correct some expected behaviour). This argument is optional (default = 32) imghomogeneityedgedetection y <- imghomogeneityedgedetection(x, bias=64) imghorizontalmirroring Horizontal mirror an image This function flips an image about the y axis. imghorizontalmirroring()

27 imgincreasecontrast 27 imgverticalmirroring y <- imghorizontalmirroring(x) imgincreasecontrast Increase contrast This function increases an image contrast, augmenting pixel values differences between given limits (in a linear fashion). imgincreasecontrast(, min_limit, max_limit) min_limit max_limit The minimum limit to apply lineal modification The maximum limit to apply lineal modification imgdecreasecontrast r_inc_contrast r_dec_contrast

28 28 imgkirsch y <- imgincreasecontrast(x, 60, 200) imgincreaseintensity Increase intensity This function increases an image intensity by a given factor. imgincreaseintensity(, percentage) percentage A non negative value representing the intensity percentage to be increased. 1 stands for 100% (eg. 0.5 = 50%) imgdecreaseintensity r_inc_intensity r_dec_intensity y <- imgincreaseintensity(x, 0.3) imgkirsch Kirsch Edge Detection Method This function enhaces image s edges by convoluting with the Kirsch method. Base matrix is:

29 imgmarrhildreth imgkirsch() y <- imgkirsch(x) imgmarrhildreth Marr-Hildreth Edge Detection Method This function does edge detection using the Marr-Hildreth algorithm. imgmarrhildreth(, sigma) sigma The standard deviation of Gaussian for convolution y <- imgmarrhildreth(x, 2)

30 30 imgmedianshrink imgmaximum Calculates image maximum This function calculates the maximum of the given images and returns a new image. imgmaximum(_list) _list An image list y <- imgmaximum(list(x, x)) imgmedianshrink Shrink an image This function shrinks an image using the median and returns a new image. imgmedianshrink(, x_scale, y_scale) x_scale y_scale The horizontal scale factor The vertical scale factor

31 imgmultiply 31 Note The scale factors are expected to be less than 1. imgaverageshrink imgnearestneighborscale imgbilinearscale imgcubicscale y <- imgmedianshrink(x, 0.5, 0.5) imgmultiply Multiply two images This function multiplies two images and returns a new image. imgmultiply(1, 2) 1 2 The first image The second image Note To multiply an image by a constant c you can just do:»> * c. y <- imgmultiply(x, x)

32 32 imgnearestneighborscale imgnearestneighborrotate Rotate an image This function rotates an image using nearest neighbor interpolation and returns a new image. imgnearestneighborrotate(, angle) angle The clockwise deg angle to rotate imgrotate imgbilinearrotate imgcubicrotate imgsplinerotate imgrotate90clockwise imgrotate90counterclockwise y <- imgnearestneighborrotate(x, 45) imgnearestneighborscale Scale an image This function scales an image using nearest neighbor interpolation and returns a new image. imgnearestneighborscale(, x_scale, y_scale)

33 imgnegative 33 x_scale y_scale The horizontal scale factor The vertical scale factor Note The scale factors are expected to be greater than 1. To reduce an image use the minification functions instead. imgscale imgbilinearscale imgcubicscale imgsplinescale imgmedianshrink imgaverageshrink y <- imgnearestneighborscale(x, 1.5, 1.5) imgnegative Negate an image This function negates an image. imgnegative()

34 34 imgnormalize r_negative r_negative_lut y <- imgnegative(x) imgnormalize Normalization for vector and matrix This function normalizes image so that the minimum value is 0 and the maximum value is 1. imgnormalize(x) x Data of the same type as x, in which minimum value is 0 and maximum value is 255. data(logo) plot(imgnormalize(logo))

35 imgprewitt 35 imgor Or two images This function does a logic OR between two images and returns a new image. imgor(1, 2) 1 2 The first image The second image imgand imgxor y <- imgor(x, x) imgprewitt Prewitt Edge Detection Method This function enhaces image s edges by convoluting with the Prewitt method matrices: H_r H_c

36 36 imgprewittcompassgradient imgprewitt() y <- imgprewitt(x) imgprewittcompassgradient Prewitt Compass Gradient Edge Detection Method This function enhaces image s edges by convoluting with the Prewitt method. Base matrix is: imgprewittcompassgradient() y <- imgprewittcompassgradient(x)

37 imgrgb2grey 37 imgrgb2grey Convert color imagedata to grey imagedata This function convert color imagedata to grey imagedata. imgrgb2grey(x, coefs=c(0.30, 0.59, 0.11)) x coefs The coefficients for red, green and blue bands grey imagedata plot(imgrgb2grey(x)) imgredband Return the image red band This function returns the red band of the imagedata. imgredband(x) x

38 38 imgroberts grey imagedata plot(imgredband(x)) imgroberts Roberts Edge Detection Method This function enhaces image s edges by convoluting with the Roberts method matrices: H_r H_c imgroberts() y <- imgroberts(x)

39 imgrobinson5level 39 imgrobinson3level Robinson 3-level Edge Detection Method This function enhaces image s edges by convoluting with the Robinson 3-level method. Base matrix is: imgrobinson3level() y <- imgrobinson3level(x) imgrobinson5level Robinson 5-level Edge Detection Method This function enhaces image s edges by convoluting with the Robinson 5-level method. Base matrix is:

40 40 imgrotate imgrobinson5level() y <- imgrobinson5level(x) imgrotate Rotate an image This function rotates an image using the given interpolation and returns a new image. imgrotate(, angle, interpolation) angle The clockwise deg angle to rotate interpolation The interpolation method: nearestneighbor bilinear cubic spline imgnearestneighborrotate imgbilinearrotate imgcubicrotate imgsplinerotate imgrotate90clockwise imgrotate90counterclockwise

41 imgrotate90clockwise 41 y <- imgrotate(x, 45, 'spline') imgrotate90clockwise Rotate an image This function rotates the image 90 degrees clockwise. imgrotate90clockwise() imgrotate90counterclockwise y <- imgrotate90clockwise(x)

42 42 imgscale imgrotate90counterclockwise Rotate an image This function rotates the image 90 degrees counter-clockwise. imgrotate90counterclockwise() imgrotate90clockwise y <- imgrotate90counterclockwise(x) imgscale Scale an image This function scales an image using the given interpolation and returns a new image. imgscale(, x_scale, y_scale, interpolation)

43 imgsharpen 43 Note x_scale The horizontal scale factor y_scale The vertical scale factor interpolation The interpolation method: nearestneighbor bilinear cubic spline The scale factors are expected to be greater than 1. To reduce an image use the minification functions instead. imgnearestneighborscale imgbilinearscale imgcubicscale imgsplinescale imgmedianshrink imgaverageshrink y <- imgscale(x, 1.5, 1.5, 'bilinear') imgsharpen Sharpens an image with selected mask This function sharpens an image by convoluting with one of the following matrices: imgsharpen (, mask)

44 44 imgshencastan mask The matrix to be used in the convolution. Must be one of 1, 2, 3 (default=1) y <- imgsharpen(x, 2) imgshencastan Shen-Castan Edge Detection Method This function does edge detection using the Shen-Castan algorithm. imgshencastan(, smooth_factor=0.9, thin_factor=2, adapt_window=7, thresh_rat smooth_factor The smooth factor thin_factor The thinning factor adapt_window The size of the window for adaptive gradient thresh_ratio The percentage of pixels to be above high threshold do_hysteresis If true, do hysteresis y <- imgshencastan(x)

45 imgsplinerotate 45 imgsobel Sobel Edge Detection Method This function enhaces image s edges by convoluting with the Sobel method matrices: H_r H_c imgsobel() y <- imgsobel(x) imgsplinerotate Rotate an image This function rotates an image using b-spline interpolation and returns a new image. imgsplinerotate(, angle) angle The clockwise deg angle to rotate

46 46 imgsplinescale imgrotate imgnearestneighborrotate imgbilinearrotate imgcubicrotate imgrotate90clockwise imgrotate90counterclockwise y <- imgsplinerotate(x, 45) imgsplinescale Scale an image This function scales an image using b-spline interpolation and returns a new image. imgsplinescale(, x_scale, y_scale) x_scale y_scale The horizontal scale factor The vertical scale factor Note The scale factors are expected to be greater than 1. To reduce an image use the minification functions instead. imgscale imgnearestneighborscale imgbilinearscale imgcubicscale imgmedianshrink imgaverageshrink

47 imgstdblur 47 y <- imgsplinescale(x, 1.5, 1.5) imgstdblur Blurs an image This function blurs an image by convoluting with a average square matrix imgstdblur(, dim) dim Square matrix dimension (optional, default = 5) imgblur y <- imgstdblur(x, 3)

48 48 imgtranslate imgthreshold Threshold an image This function thresholds an image using a given filter. imgthreshold(, thr_value) thr_value Filter value for thresholding r_threshold y <- imgthreshold(x, 80) imgtranslate Translate an image block This function translates an image block and returns a new image. imgtranslate(, x_start, y_start, x_end, y_end, t_width, t_height)

49 imgunsharpen 49 x_start y_start x_end y_end t_width t_height Upper left x coordinate of source block Upper left y coordinate of source block Upper left x coordinate of destination block Upper left y coordinate of destination block Width of the block to move Height of the block to move y <- imgtranslate(x, 100, 100, 200, 200, 50, 50) imgunsharpen Unsharpens an image with selected mask This function unsharpens an image by convoluting with one of the following matrices: Performs a difference between original image and sharpen convolved image with the specified mask imgunsharpen (, mask) mask The matrix to be used in the convolution. Must be one of 1, 2, 3 (default=1)

50 50 imgverticalmirroring y <- imgunsharpen(x, 2) imgverticalmirroring Vertical mirror an image This function flips an image about the x axis. imgverticalmirroring() imghorizontalmirroring y <- imgverticalmirroring(x)

51 imgxor 51 imgxor Xor two images This function does a logic XOR between two images and returns a new image. imgxor(1, 2) 1 2 The first image The second image imgor imgand y <- imgxor(x, x) logo R logo imagedata data object of R logo of the size 101x77. data(logo) Format imagedata

52 52 print.imagedata data(logo) plot(logo) plot.imagedata Plotting an imagedata object This function outputs an imagedata object as an image. plot.imagedata(x,...) x... Plotting options imagedata plot(x) print.imagedata Print information on a given imagedata object This function outputs information on a given imagedata object. print.imagedata(x,...)

53 r_dec_contrast 53 x... Ignored imagedata print(x) r_dec_contrast Decrease contrast This function decreases an image contrast, leaving each pixel value between given values. r_dec_contrast(, min_desired, max_desired) min_desired max_desired The min value The max value Note This is the R implementation of imgdecreasecontrast. imgdecreasecontrast imgincreasecontrast r_inc_contrast

54 54 r_dec_intensity y <- r_dec_contrast(x, 60, 200) r_dec_intensity Decrease intensity This function decreases an image intensity by a given factor. r_dec_intensity(, percentage) percentage A non negative value representing the intensity percentage to be decreased. 1 stands for 100% (eg. 0.5 = 50%). Note This is the R implementation of imgdecreaseintensity. imgdecreaseintensity imgincreaseintensity r_inc_intensity y <- r_dec_intensity(x, 0.3)

55 r_gamma 55 r_gamma Gamma correct an image This function applies gamma operation to a given image. Each pixel value is taken to the inverse of gamma_value-th exponent r_gamma(, gamma_value) gamma_value A non negative value representing operation gamma value Note This is the R implementation of imggamma. imggamma y <- r_gamma(x, 1.3)

56 56 r_imgaverage r_imgadd Add two images This function adds two images and returns a new image. r_imgadd(1, 2) 1 2 The first image The second image Note This is the R implementation of imgadd. imgadd y <- r_imgadd(x, x) r_imgaverage Average images This function calculates the average of the given images and returns a new image. r_imgaverage(_list)

57 r_imgdiffer 57 _list An image list Note This is the R implementation of imgaverage. imgaverage y <- r_imgaverage(list(x, x)) r_imgdiffer Substract two images This function substracts two images and returns a new image, 1-2. r_imgdiffer(1, 2) 1 2 The first image The second image Note This is the R implementation of imgdiffer.

58 58 r_imgmaximum imgdiffer y <- r_imgdiffer(x, x) r_imgmaximum Images maximum This function calculates the maximum of the given images and returns a new image. r_imgmaximum(_list) _list An image list Note This is the R implementation of imgaverage. imgmaximum y <- r_imgmaximum(list(x, x))

59 r_inc_contrast 59 r_inc_contrast Increase contrast This function increases an image contrast, augmenting pixel values differences between given limits (in a linear fashion). r_inc_contrast(, min_limit, max_limit) min_limit max_limit The minimum limit to apply lineal modification The maximum limit to apply lineal modification Note This is the R implementation of imgincreasecontrast. imgincreasecontrast imgdecreasecontrast r_dec_contrast y <- r_inc_contrast(x, 60, 200)

60 60 r_inc_intensity r_inc_intensity Increase intensity This function increases an image intensity by a given factor. r_inc_intensity(, percentage) percentage A non negative value representing the intensity percentage to be increased. 1 stands for 100% (eg. 0.5 = 50%). Note This is the R implementation of imgincreaseintensity. imgincreaseintensity imgdecreaseintensity r_dec_intensity y <- r_inc_intensity(x, 0.3)

61 r_look_up_table 61 r_look_up_table Transforms an image by a given look-up table This function applies a transformation to an image using a given look-up table. r_look_up_table(, table) table Look up table which determines the image operation to be applied lut <- seq(255, 0, by=-1) y <- r_threshold(x, lut) r_negative Negate an image This function negates an image. r_negative()

62 62 r_negative_lut Note This is the R implementation of imgnegative. imgnegative r_negative_lut y <- r_negative(x) r_negative_lut Negate an image This function negates an image. r_negative_lut() Note This is the R implementation of imgnegative using look up tables. imgnegative r_negative y <- r_negative_lut(x)

63 r_threshold 63 r_threshold Threshold an image This function thresholds an image using a given filter. r_threshold(, thr_value) thr_value Filter value for thresholding Note This is the R implementation of imgthreshold. imgthreshold y <- r_threshold(x, 80) readjpeg Read jpeg file This function reads a jpeg image file and. readjpeg(filename)

64 64 readtiff filename filename of JPEG image imagedata plot(x) readtiff Read tiff file This function reads a tiff image file and. readtiff(filename) filename filename of TIFF image imagedata x <- readtiff(system.file("data", "violet.tif", package="biops")) plot(x)

65 writejpeg 65 writejpeg Write jpeg file This function writes an imagedata object into a jpeg image file. writejpeg(filename, ) filename filename of JPEG image imagedata to write readjpeg writejpeg("new_image.jpg", x) writetiff Write tiff file This function writes an imagedata object into a tiff image file. writetiff(filename, ) filename filename of TIFF image imagedata to write readtiff

66 66 writetiff x <- readtiff(system.file("data", "violet.tif", package="biops")) writetiff("new_image.tif", x)

67 Index Topic IO readjpeg, 61 readtiff, 62 writejpeg, 63 writetiff, 63 Topic datasets logo, 49 Topic logic imgand, 5 imgnegative, 31 imgor, 33 imgxor, 49 r_negative, 59 r_negative_lut, 60 Topic math imgadd, 5 imgaverage, 6 imgaverageshrink, 7 imgbilinearrotate, 8 imgbilinearscale, 8 imgblur, 10 imgboost, 11 imgcanny, 12 imgconvolve, 13 imgcrop, 14 imgcubicrotate, 14 imgcubicscale, 15 imgdecreasecontrast, 16 imgdecreaseintensity, 17 imgdiffer, 17 imgdifferenceedgedetection, 18 imgdivide, 19 imgfreichen, 19 imggamma, 20 imghighpassfilter, 22 imghomogeneityedgedetection, 24 imghorizontalmirroring, 24 imgincreasecontrast, 25 imgincreaseintensity, 26 imgkirsch, 26 imgmarrhildreth, 27 imgmaximum, 28 imgmedianshrink, 28 imgmultiply, 29 imgnearestneighborrotate, 30 imgnearestneighborscale, 30 imgprewitt, 33 imgprewittcompassgradient, 34 imgroberts, 36 imgrobinson3level, 37 imgrobinson5level, 37 imgrotate, 38 imgrotate90clockwise, 39 imgrotate90counterclockwise, 40 imgscale, 40 imgsharpen, 41 imgshencastan, 42 imgsobel, 43 imgsplinerotate, 43 imgsplinescale, 44 imgstdblur, 45 imgthreshold, 46 imgtranslate, 46 imgunsharpen, 47 imgverticalmirroring, 48 r_dec_contrast, 51 r_dec_intensity, 52 r_gamma, 53 r_imgadd, 54 r_imgaverage, 54 r_imgdiffer, 55 r_imgmaximum, 56 r_inc_contrast, 57 r_inc_intensity, 58 r_look_up_table, 59 67

68 68 INDEX r_threshold, 61 Topic misc imagedata, 4 imagetype, 3 imgblueband, 9 imggetrgbfrombands, 21 imggreenband, 22 imghistogram, 23 imgnormalize, 32 imgredband, 35 imgrgb2grey, 35 plot.imagedata, 50 print.imagedata, 50 Topic package biops-package, 1 biops (biops-package), 1 biops-package, 1 hist, 23 imagedata, 4, 50, 51, 62 imagetype, 3 imgadd, 5, 54 imgand, 5, 33, 49 imgaverage, 6, 55 imgaverageshrink, 7, 9, 15, 29, 31, 41, 44 imgbilinearrotate, 8, 15, 30, 38, 44 imgbilinearscale, 7, 8, 15, 29, 31, 41, 44 imgblueband, 9 imgblur, 10, 45 imgboost, 11 imgcanny, 12 imgconvolve, 13 imgcrop, 14 imgcubicrotate, 8, 14, 30, 38, 44 imgcubicscale, 7, 9, 15, 29, 31, 41, 44 imgdecreasecontrast, 16, 25, 51, 57 imgdecreaseintensity, 17, 26, 52, 58 imgdiffer, 17, 56 imgdifferenceedgedetection, 18 imgdivide, 19 imgfreichen, 19 imggamma, 20, 53 imggetrgbfrombands, 21 imggreenband, 22 imghighpassfilter, 12, 22 imghistogram, 23 imghomogeneityedgedetection, 18, 24, 24 imghorizontalmirroring, 24, 48 imgincreasecontrast, 16, 25, 51, 57 imgincreaseintensity, 17, 26, 52, 58 imgkirsch, 26 imgmarrhildreth, 27 imgmaximum, 28, 56 imgmedianshrink, 7, 9, 15, 28, 31, 41, 44 imgmultiply, 29 imgnearestneighborrotate, 8, 15, 30, 38, 44 imgnearestneighborscale, 7, 9, 15, 29, 30, 41, 44 imgnegative, 31, 60 imgnormalize, 32 imgor, 5, 33, 49 imgprewitt, 33 imgprewittcompassgradient, 34 imgredband, 35 imgrgb2grey, 35 imgroberts, 36 imgrobinson3level, 37 imgrobinson5level, 37 imgrotate, 8, 15, 30, 38, 44 imgrotate90clockwise, 8, 15, 30, 38, 39, 40, 44 imgrotate90counterclockwise, 8, 15, 30, 38, 39, 40, 44 imgscale, 9, 15, 31, 40, 44 imgsharpen, 41 imgshencastan, 42 imgsobel, 43 imgsplinerotate, 8, 15, 30, 38, 43 imgsplinescale, 9, 15, 31, 41, 44 imgstdblur, 10, 45 imgthreshold, 46, 61 imgtranslate, 46 imgunsharpen, 47 imgverticalmirroring, 25, 48 imgxor, 5, 33, 49 logo, 49 plot.imagedata, 4, 50 print.imagedata, 4, 50 r_dec_contrast, 16, 25, 51, 57

69 INDEX 69 r_dec_intensity, 17, 26, 52, 58 r_gamma, 20, 53 r_imgadd, 54 r_imgaverage, 54 r_imgdiffer, 55 r_imgmaximum, 56 r_inc_contrast, 16, 25, 51, 57 r_inc_intensity, 17, 26, 52, 58 r_look_up_table, 59 r_negative, 32, 59, 60 r_negative_lut, 32, 60, 60 r_threshold, 46, 61 readjpeg, 61, 63 readtiff, 62, 63 writejpeg, 63 writetiff, 63