To get started, import Data.Image
or Data.Image.Boxed
.
To use unm-hip interactively in ghci, import Data.Image.Interactive
. This provides three useful functions: display
, setDisplayProgram
, and plotHistograms
.
setDisplayProgram :: String -> Bool -> IO ()
Sets the program to use when making a call to display
and specifies if the program can accept an image via stdin. If it cannot, then a temporary file will be created and passed as an argument instead. By default, ImageMagick (display
) is the default program to use and it is read using stdin.
*Main> setDisplayProgram "gimp" False
*Main> setDisplayProgram "xv" False
*Main> setDisplayProgram "display" True
display :: DisplayFormat df => df -> IO (Handle, Handle, Handle, ProcessHandle)
Makes a call to the current display program to be displayed. If the program cannot read from standard in, a file named .tmp-img is created and used as an argument to the program.
makeImage :: Image i => Int -> Int -> PixelOp (Pixel i) -> i
Given an Int
m, Int
n, and a PixelOp
f, makeImage
returns an Image with dimensions m x n and the Pixel
value at
each (i, j) is f i j
.
*Main> let grad = makeImage 128 128 (\ r c -> fromIntegral (r + c)) :: GrayImage
*Main> grad
< Image 128x128 >
*Main> display grad
pii :: Complex Double
pii = 0 :+ pi
harmonicSignal :: Double -> Double -> Int -> Int -> Complex Double
harmonicSignal u v m n = exp ((2*pii) * ((u*(fromIntegral m) + v*(fromIntegral n)) :+ 0))
*Main> let signal = makeImage 128 128 (harmonicSignal (3 / 128) (2 / 128)) :: ComplexImage
*Main> signal
*Main> signal
< Image 128x128 >
*Main> display signal
readImage :: FilePath -> IO GrayImage
Given the file path to a file containing an image stored in ASCII .pgm format, readImage
reads the file and returns the Image
. For example,
*Main> frog <- readImage "images/frog.pgm"
*Main> display frog
writeImage :: DisplayFormat df => FilePath -> df -> IO ()
Given a filename and an Image,
writeImage
creates a file representing the image in ASCII .pgm format for GrayImage
s and .ppm for ColorImage
and ComplexImage
. Note: Images saved this way are normalized to integers in the range 0 to 255; this may result in loss of detail.
*Main> writeImage "frog.pgm" frog
creates a file which looks like this:
P2
242 225
255
151 151 151 151 151 150 150 149 148 147 146 145 145 142 142
143 145 148 152 156 158 159 159 159 159 157 155 152 150 153
152 151 149 149 149 149 150 149 149 149 149 149 149 149 149
149 146 144 141 138 136 133 132 136 136 136 136 136 136 136
136 139 138 138 138 137 136 136 136 135 135 136 136 137 137
138 138 138 137 138 137 138 137 138 137 135 134 134 134 138
141 147 150 149 147 143 138 134 132 131 130 129 129 130 132
134 136 137 137 137 137 138 139 142 145 147 149 145 146 150
153 156 159 161 163 156 158 161 163 167 170 174 175 181 183
.
.
.
ref :: Image i => i -> Int -> Int -> Pixel i
Given an image, a positive Int
i, and a positive Int
j, ref
returns the Pixel
value at location (i, j).
*Main> ref frog 100 100
56.0
ref' :: ref' :: GrayImage -> Double -> Double -> Double
Given a GrayImage
, a positive Double
i, and a positive Double
j, ref'
returns the bilinear interpolated Pixel
value at location (i, j).
*Main> ref' frog 100 100
56.0
rows :: Image i => i -> Int
Given an Image
, rows
returns the number of rows of in the Image
.
For example,
*Main> rows frog
225
cols :: Image i => i -> Int
Given an Image
, cols
returns the number of columns of in the Image
.
For example,
*Main> cols frog
242
transpose :: Image img => img -> img
Given an Image
img, transpose
returns an Image
created by interchanging the rows and columns of the Image
, i.e., the value at location (i, j) of the result Image
is the value of the img at location (j, i).
For example,
*Main> transpose frog
< Image 242x225 >
*Main> display . transpose $ frog
convolveRows :: (Num (Pixel img), Image img) => [Pixel img] -> img -> img
Given a list consisting solely of Pixel
values representing a 1D convolution kernel and an Image
, convolveRows
returns the 1D discrete periodic convolution of the rows of the Image
with the kernel.
For example,
*Main> convolveRows [1, -1] frog
< Image 225x242 >
*Main> display . convolveRows [1, -1] $ frog
convolveCols :: (Num (Pixel img), Image img) => [Pixel img] -> img -> img
Given a list consisting solely of Pixel
values representing a 1D convolution kernel and an Image
, convolveCols
returns the 1D discrete periodic convolution of the columns of the Image
with the kernel.
For example,
*Main> convolveCols [1, -1] frog
< Image 225x242 >
*Main> display . convolveCols [1, -1] $ frog
*Main> let dx = convolveRows [1, -1] frog
*Main> let dy = convolveCols [1, -1] frog
*Main> let grad = imageMap sqrt ((dx * dx) + (dy * dy)) :: GrayImage
*Main> grad
< Image 225x242 >
*Main> display grad
convolve :: (Num (Pixel img), Image img) => \[\[Pixel img\]\] -> img -> img
Given a 2D list consisting solely of Pixel
s representing a 2D convolution kernel and an Image
, convolve
returns the 2D discrete periodic convolution of the Image
with the kernel.
For example,
*Main> convolve [[1, 1, 1], [1, -8, 1], [1, 1, 1]] frog
< Image 225x242 >
*Main> display . convolve [[1, 1, 1], [1, -8, 1], [1, 1, 1]] $ frog
downsampleCols :: Image img => img -> img
Given img, downsampleCols
returns the image created by discarding the odd numbered rows, i.e., the value at location (i, j) of the result image is the value of img at location (2i, j).
For example,
*Main> downsampleCols frog
< Image 112x242 >
*Main> display . downsampleCols $ frog
downsampleRows :: Image img => img -> img
Given img, downsampleRows
returns the image created by discarding the odd numbered columns, i.e., the value at location (i, j) is the value of img at location (i, 2j).
For example,
*Main> downsampleRows frog
< Image 225x121 >
*Main> display . downsampleRows $ frog
downsample :: Image img => img -> img
*Main> let tinyFrog = downsample frog
*Main> tinyFrog
< Image 112x121 >
*Main> display tinyFrog
upsampleCols :: (Monoid (Pixel img), Image img) => img -> img
Given img, upsampleCols
returns an Image
with twice the number of rows where the value at location (i, j) of the result Image
is the value of img at location (i/2, j) if i is even and mempty
otherwise.
For example,
*Main> upsampleCols tinyFrog
< Image 224x121 >
*Main> display . upsampleCols $ tinyFrog
upsampleRows :: (Monoid (Pixel img), Image img) => img -> img
Given img, upsampleRows
returns an Image
with twice the number of columns where the value at location (i, j) of the result Image
is the value of img at location (i, j/2) if j is even and mempty
otherwise.
For example,
*Main> upsampleRows tinyFrog
< Image 112x242 >
*Main> display . upsampleRows $ tinyFrog
upsample :: (Monoid (Pixel img), Image img) => img -> img
Given img, upsample
returns anImage
with twice the number ofrows and columns where the value at location (i, j) of the resulting image is the value of img at location (i/2, j/2) if i and j are are even and mempty
otherwise.
For example,
*Main> upsample tinyFrog
< Image 224x242 >
*Main> display . upsample $ tinyFrog
pad :: (Monoid (Pixel img), Image img) => Int -> Int -> img -> img
Given m, n, and img, pad
returns an Image
with m rows and n columns where the value at location (i, j) of the result Image
is the value of img at location (i, j) if i is less than m and j is less than n.
and mempty
otherwise.
For example,
*Main> pad 200 200 tinyFrog
< Image 200x200 >
*Main> display . pad 200 200 $ tinyFrog
crop :: Image img => Int -> Int -> Int -> Int -> img -> img
Given a i0, j0, m, n, and img, crop
returns an Image
with m rows and n columns where the value at location (i, j) of the result Image
is the value of img at location (i0 + i, j0 + j).
For example,
*Main> let frogPart = crop 64 64 128 128 frog
*Main> frogPart
< Image 128x128 >
*Main> display frogPart
leftToRight :: Image img => img -> img -> img<
Given two Images
with the same number of rows X and Y, leftToRight
returns an Image
that is the concatenation of the two Images
from left to right. There is a convenience function, leftToRight'
that takes a pair, triple, or list of Images
and displays them left to right.
For example,
*Main> leftToRight tinyFrog tinyFrog
< Image 112x242 >
*Main> display . leftToRight tinyFrog $ tinyFrog
topToBottom :: Image img => img -> img -> img
Given two Images
with the same number of columns X and Y, topToBottom
returns an image that is the concatenation of the two images from top to bottom. There is a convenience function, topToBottom' that takes a pair, triple, or list of Images
and displays them top to bottom.
For example,
*Main> topToBottom tinyFrog tinyFrog
< Image 224x121 >
*Main> display . topToBottom tinyFrog $ tinyFrog
makeFilter :: Image img => Int -> Int -> PixelOp (Pixel img) -> img
Given a positive Integer
m, a positive Integer
n, and a function returning a Pixel
value, makeFilter
returns an Image
with m rows and n columns. Let x equal i if i is less than m/2 and i - m otherwise and let y equal j if j is less than n/2 and j - n otherwise. To match the periodicity of the 2D discrete Fourier spectrum, the value of the result Image
at location (i, j) is computed by applying the function to x and y, e.g., the value at location (0, 0) is the result of applying the function to 0 and 0, the value at (m-1, n-1) is the result of applying function to -1 and -1.
For example,
*Main Data.Complex> let filter = makeFilter 128 128 (\ i j -> fromIntegral (i + j)) :: GrayImage
*Main Data.Complex> filter
< Image 128x128 >
*Main Data.Complex> display filter
laplacianOfGaussian stddev i j =
let r = fromIntegral (i*i + j*j)
x = (r / 2.0) / stddev
in (((-pi) / stddev) / stddev) * (1 - x) * (exp (-x))
*Main Data.Complex> let d2g = makeFilter 128 128 (laplacianOfGaussian 8) :: ComplexImage
*Main Data.Complex> d2g
< Image 128x128 >
*Main Data.Complex> display d2g
fft :: (Image img, Image img', ComplexPixel (Pixel img), Pixel img' ~ Complex (Value (Pixel img))) => img -> img'
Given an Image
whose Pixel
s can be converted to a complex value, fft
returns an Image
with ComplexPixel
s representing its 2D discrete Fourier transform (DFT). Because the DFT is computed using the Fast Fourier Transform (FFT) algorithm, the number of rows and columns of the Image
must both be powers of two, i.e., 2K where K is an integer.
For example,
*Main> let logFrog = magnitude . imageMap log . fft $ frogpart
*Main> logFrog
< Image 128x128 >
*Main> display logFrog
*Main> fft d2g
< Image 128x128 >
*Main> display . fft $ d2g
gaussian variance i j =
let r = fromIntegral (i*i + j*j)
x = (r / (2*pi)) / variance
in exp (-x)
*Main> let g = makeFilter 128 128 (gaussian 8) :: GrayImage
*Main> display g
*Main> fft g
< Image 128x128 >
*Main> display . fft $ g
ifft :: (Image img, Image img', ComplexPixel (Pixel img), Pixel img' ~ Complex (Value (Pixel img))) => img -> img'
Given an Image
, ifft
returns a complex Image
representing its 2D inverse discrete Fourier transform (DFT). Because the inverse DFT is computed using the Fast Fourier Transform (FFT) algorithm, the number of rows and columns of Image
must both be powers of two, i.e., 2K
where K is an integer.
For example,
*Main> ifft ((fft frogPart) * (fft d2g))
< Image 128x128 >
*Main> display $ ifft ((fft frogPart) * (fft d2g))
*Main> ifft ((fft frogPart) * (fft g))
< Image 128x128 >
*Main> display $ ifft ((fft frogPart) * (fft g))
realPart :: (Image img, Image img', ComplexPixel (Pixel img), Pixel img' ~ Value (Pixel img)) => img -> img'
Given a complex Image
, returns a real Image
representing the real part of the Image
.
For example,
*Main> let cosine = realPart signal :: GrayImage
*Main> cosine
< Image 128x128 >
*Main> display cosine
*Main> display . realPart . ifft $ (fft frogpart) * (fft d2g)
*Main> display . realPart . ifft $ (fft frogpart) * (fft g)
imagPart :: (Image img, Image img', ComplexPixel (Pixel img), Pixel img' ~ Value (Pixel img)) => img -> img'
Given a complex Image
, imagPart
returns a real Image
representing the imaginary part of the Image
.
For example,
*Main> let sine = imagPart signal :: GrayImage
*Main> sine
< Image 128x128 >
*Main> display sine
complex :: (Image img, Image img', Pixel img' ~ C.Complex (Pixel img)) => img -> img -> img'
Given an Image
representing the real part of a complex Image
, and an Image
representing the imaginary part of a complex Image
, complex
returns a complex Image
.
For example,
*Main> complex cosine sine :: ComplexImage
< Image 128x128 >
*Main> display (complex cosine sine :: ComplexImage)
complexImageToRectangular :: (Image img, Image img', ComplexPixel (Pixel img), Pixel img' ~ Value (Pixel img)) => img -> (img', img')
Given a complex Image
, complexImageToRectangular
returns a pair of real Images
each representing a component of the complex Image
(real, imaginary).
For example,
*Main> leftToRight' . complexImageToRectangular $ signal
< Image 128x256 >
*Main> display . leftToRight' . complexImageToRectangular $ signal
![complesSignalToRectangular][]
magnitude :: (Image img, Image img', ComplexPixel (Pixel img), Pixel img' ~ Value (Pixel img)) => img -> img'
Given a complex Image
, returns a real Image
representing the magnitude of the Image
.
angle :: (Image img, ComplexPixel (Pixel img), Image img', Pixel img' ~ Value (Pixel img)) => img -> img'
Given a complex Image
, angle
returns a real Image
representing the angle of the Image
.
For example,
*Main> angle signal
< Image 128x128 >
*Main> display (angle signal :: GrayImage)
complexImageToPolar :: (Image img, ComplexPixel (Pixel img), Image img', Pixel img' ~ Value (Pixel img)) => img -> (img', img')
Given a complex Image
, complexImageToPolar
returns a pair of real Image
s each representing the component (magnitude, phase) of the Image
.
*Main> complexImageToPolar signal
(< Image 128x128 >,< Image 128x128 >)
*Main> display . leftToRight' . complexImageToPolar $ signal
(==) :: (==) :: Eq a => a -> a -> Bool
Image
s installed in the Eq
type class (Boxed images) may be compared using the (==)
. This returns True
if and only if the Image
s are of equal dimension and for each Pixel
(i, j) in the two Image
s are (==)
.
(<) :: Ord a => a -> a -> Bool
Image
s installed in the Ord
type class (Boxed images) may be compared using (<)
. This returns True
if and only if the Image
s are of equal dimension and for each Pixel
(i, j) in the two Image
s are (<)
.
(>) :: Ord a => a -> a -> Bool
Image
s installed in the Ord
type class (Boxed images) may be compared using (>)
. This returns True
if and only if the Image
s are of equal dimension and for each Pixel
(i, j) in the two Image
s are (>)
.
(+) :: Num a => a -> a -> a
Any two Image
s installed in the Num
type class (any two Boxed images) may be added if their dimensions match. For each (i, j) the resulting Pixel
will be the sum of the Pixel
s from the given Image
s.
For example,
*Main> callisto <- readImage "images/callisto.pgm"
*Main> display callisto
*Main> ganymede <- readImage "images/ganymede.pgm"
*Main> display ganymede
*Main> callisto + ganymede
< Image 128x128 >
*Main> display $ callisto + ganymede
(+.) :: (Num (Pixel i), Image i) => Pixel i -> i -> i
Given a Pixel
value and an Image
, (+.)
performs scalar addition to each Pixel
in an Image
and returns the result. Note: there is a flipped version of this function (.+)
.
(-) :: Num a => a -> a -> a
Any two Image
s installed in the Num
type class (any two Boxed images) may be subtracted if their dimensions match. For each (i, j) the resulting Pixel
will be the difference of the two Pixel
s from the given Image
.
For example,
*Main> display $ callisto - ganymede
(-.) :: (Num (Pixel i), Image i) => Pixel i -> i -> i
Given a Pixel
value and an Image
, (-.)
performs scalar subtraction to each Pixel
in an Image
and returns the result. Note: there is a flipped version of this function (.-)
.
(*) :: Num a => a -> a -> a
Any two Image
s installed in the Num
type class (any two Boxed images) may be multiplied if their dimensions match. For each (i, j) the resulting Pixel
will be the product of the two Pixel
s from the given Image
s.
For example,
*Main> display (callisto * ganymede)
(*.) :: (Num (Pixel i), Image i) => Pixel i -> i -> i
Given a Pixel
value and an Image
, (*.)
performs scalar multiplication to each Pixel
in an Image
and returns the result. Note: there is a flipped version of this function (.*)
.
(/) :: Fractional a => a -> a -> a
Any two Image
s installed in the Num
type class (any two Boxed images) may be divided if their dimensions match. For each (i, j) the resulting Pixel
will be the quotient of the two Pixel
s from the given Image
s.
For example,
*Main> display (callisto / ganymede)
(/.) :: (Fractional (Pixel i), Image i) => Pixel i -> i -> i
Given a Pixel
value and an Image
, (/.)
performs scalar division to each pixel in an Image
and returns the result. Note: there is a flipped version of this function (./)
.
arrayToImage :: Image img => Array (Int, Int) (Pixel img) -> img
Given a two dimensional array of Pixel
values indexed by pairs of Int
s where the fst
is the row and snd
is the column, arrayToImage
returns an Image
.
For example,
*Main> let array = listArray ((0,0),(127,127)) [0..] :: Array (Int,Int) Double
*Main> arrayToImage array :: GrayImage
< Image 128x128 >
*Main> display (arrayToImage array :: GrayImage)
imageToArray :: Image img => img -> Array (Int, Int) (Pixel img)
Given img, imageToArray
returns an two dimensional array of Pixel
values indexed by pairs of Int
s where the fst
is the row and snd
is the column.
*Main> let arr = listArray ((0,0),(2,2)) [0..] :: Array (Int, Int) Double
*Main> imageToArray (arrayToImage arr :: GrayImage)
array ((0,0),(2,2)) [((0,0),0.0),((0,1),1.0),((0,2),2.0),((1,0),3.0),((1,1),4.0),((1,2),5.0),((2,0),6.0),((2,1),7.0),((2,2),8.0)]
(>.) :: (Ord (Pixel img), Image img, BinaryPixel (Pixel img)) => Pixel img -> img -> img
Given a Pixel
p and an Image
img, return a BinaryPixel
Image
where the Pixel
at (i, j) is on if p is greater than the corresponding Pixel
in img at (i,j) and off otherwise. Note: there is a variation of (>.)
named (.>)
where the arguments are flipped.
*Main> stop <- readColorImage "images/stop.ppm"
*Main> display stop
*Main> let (r,g,b) = colorImageToRGB stop
*Main> let binaryStop = (r + g + b) .> 400
*Main> display binaryStop
(<.) :: (Ord (Pixel img), Image img, BinaryPixel (Pixel img)) => Pixel img -> img -> img
Given a Pixel
p and an Image
img, return a BinaryPixel
Image
where the Pixel
at (i, j) is on if p is less than the corresponding Pixel
in img at (i,j) and off otherwise. Note: there is a variation of (<.)
named (.<)
where the arguments are flipped.
*Main> let (r,g,b) = colorImageToRGB stop
*Main> let invertBinaryStop = (r + g + b) .< 400
*Main> display invertBinaryStop
(<~) :: (Ord (Pixel img), Image img) => Pixel img -> img -> Bool
Given a Pixel
value p and an Image
img, return True
if and only if all values in img are greater than p. Note: there is a variation of (<~)
named(~<)
where the arguments are flipped.
(.==.) :: (Eq (Pixel img), Image img, BinaryPixel (Pixel img)) => img -> img -> img
Note to the reader, the documentation for the
(.==.)
is not correct. It will be updated shortly.Given an
Image
withPixel
s, p, and aPixel
, c, returns anImage
where eachPixel
has the value 1 if and only if p = c and 0 otherwise. Note: there is a variation of(==.)
named(.==)
in which eachPixel
in theImage
is compared to a single specifiedPixel
.
shiftRight :: Image img => Int -> img -> img
shiftRight s img = makeImage (rows img) (cols img) shift where
shift r c = ref img r c' where
c' = let sum = c + s
in if sum < (cols img) then sum else sum - (cols img)
*Main> let binaryStop = (r + g + b) .> 400
*Main> display $ (shiftRight 100 binaryStop)
*Main> display $ (shiftRight 100 binaryStop) .==. binaryStop
normalize :: (Fractional (Pixel img), MaxMin (Pixel img), Image img) => img -> img
Given img, normalize
returns an image with the same dimensions where the values have been normalized to lie in the interval [0, 1].
shrink :: (Num a, Image img, ComplexPixel (Pixel img), Image img', Pixel img' ~ C.Complex (Value (Pixel img))) => a -> img -> img'
Given a complex Image
and a real positive number x, shrink
returns a complex Image
with the same dimensions. Let z be the value of the Image
at location (i, j). The value of the complex result Image
at location (i, j) is zero if |z| < x, otherwise the result has the same phase as z but the amplitude is decreased by x.
medianFilter :: (Ord (Pixel img), Image img) => Int -> Int -> img -> img
Given two positive integers, m and n and a an Image
, medianFilter
returns an Image
with the same dimensions where each Pixel
(i, j) in Image
is replaced by the Pixel
with median value in the neighborhood of size m times n centered on (i, j).
*Main> let medianFilteredFrog = medianFilter 5 5 frog
*Main> display medianFilteredFrog
imageFold :: Image img => (Pixel img -> b -> b) -> b -> img -> b
Given a function of a Pixel
to a value of type b
which returns a value of type b
, imageFold
returns the value of type b
which results from repeatedly applying the function to:
- The result accumulated to this point. (initially the value of the first
Pixel
); - The value of the next
Pixel
.
matrixProduct :: (Num (Pixel img), Image img) => img -> img -> img
Given an Image
X1 and an Image
X2, where the number of columns of X1 equals the number of rows of X2, matrixProduct
returns an Image
representing the matrix product of X1 and X2.
*Main> display (matrixProduct frogPart frogPart)
imageMap :: (Image a, Image b) => (Pixel a -> Pixel b) -> a -> b
Given a function of a Pixel
value of type a
to a Pixel
value of type b
, and an Image
containing Pixel
values of type a
, imageMap
returns an Image
of type b
where each Pixel
in the result Image
is the result of appyling the function to each Pixel
in the given Image
. Note: Boxed images are in typeclass Functor
and Applicative
it is recommended you use fmap
instead of imageMap
for Boxed images.
*Main> let img = imageMap ((-1) *) frog :: GrayImage
*Main> display img
readColorImage :: FilePath -> IO ColorImage
Given the file path to a file containing an image stored in ASCII .ppm format, readColorImage
reads the file and returns the ColorImage
.
For example,
*Main> cacti <- readColorImage "images/cacti.ppm"
*Main> display cacti
colorImageRed :: ColorImage -> GrayImage
Given a ColorImage
, colorImageRed
returns a GrayImage
representing the red color component.
For example,
*Main> let red = colorImageRed cacti
*Main> display red
colorImageGreen :: ColorImage -> GrayImage
Given a ColorImage
, colorImageGreen
returns a GrayImage
representing the green color component
For example,
*Main> let green = colorImageGreen cacti
*Main> display green
colorImageBlue :: ColorImage -> GrayImage
Given a ColorImage
, colorImageBlue
returns a GrayImage
representing the blue color component
For example,
*Main> let blue = colorImageBlue cacti
*Main> display blue
rgbToColorImage :: (GrayImage, GrayImage, GrayImage) -> ColorImage
Given a triple containing three GrayImage
s each containing one of the color components (red, green, blue), rgbToColorImage
returns a ColorImage
.
*Main> display . rgbToColorImage $ (red,green,blue)
colorImageToRGB :: ColorImage -> (GrayImage, GrayImage, GrayImage)
Given a ColorImage
, colorImageToRGB
returns a triple containing three GrayImage
s each containing one of the color components (red, green, blue)
For example,
*Main> display . leftToRight' $ colorImageToRGB cacti
colorImageToHSI :: ColorImage -> (GrayImage, GrayImage, GrayImage)
Given a ColorImage
, colorImageToHSI
returns a triple containing three GrayImage
s each containing one of the components (hue, saturation, intensity).
For example,
*Main> let (h,s,i) = colorImageToHSI cacti
*Main> display h
*Main> display s
*Main> display i
hsiToColorImage :: (GrayImage, GrayImage, GrayImage) -> ColorImage
Given a triple containing three GrayImage
s each containing one of the color components (hue, saturation, intensity), hsiToColorImage
returns a ColorImage
.
For example,
*Main> display . hsiToColorImage $ (h, s, i)
makeHotImage :: GrayImage -> ColorImage
Given a GrayImage
, makeHotImage
returns a ColorImage
with the same dimensions. The R, G, B values of the result ColorImage
at (i, j) are determined by using the value of the GrayImage
at (i, j) to index three lookup tables. These lookup tables implement a false coloring scheme which maps small values to black, large values to white, and intermediate values to shades of red, orange, and yellow (in that order).
*Main> display . makeHotImage $ frog
dilate :: (Eq (Pixel img), Num (Pixel img), Image img, BinaryPixel (Pixel img)) => \[\[Pixel img\]\] -> img -> img
Given a 2D list consisting solely of Pixel
s representing a structuring element, and a BinaryPixel
Image
, dilate
returns the morphological dilation of the Image
with the structuring element. Note: There is a dilate'
function that uses a default structuring element of [[1,1], [1,1]]. For example,
structure = [[0, 0, 1, 0, 0],
[0, 1, 1, 1, 0],
[1, 1, 1, 1, 1],
[0, 1, 1, 1, 0],
[0, 0, 1, 0, 0]]
*Main> display . dilate structure $ binaryStop
erode :: (Eq (Pixel img), Num (Pixel img), Image img, BinaryPixel (Pixel img)) => \[\[Pixel img\]\] -> img -> img
Given a 2D list consisting solely of Pixel
s representing a structuring element, and a BinaryPixel
Image
, erode
returns the morphological erosion of the Image
with the structuring element. Note: There is a erode'
function that uses a default structuring element of [[1,1], [1,1]].
For example,
*Main> display . erode structure $ binaryStop
outline :: (Image img, BinaryPixel (Pixel img), Eq (Pixel img)) => img -> img
Given an Image
, outline
returns an Image
where edge Pixel
s are set to the value on and non-edge Pixel
s are set to the value off Pixel
(i, j) is an edge Pixel
if and only if its value is different than the value of either Pixel
(i, j+1) or Pixel
(i+1, j). Note: There is an outline'
that allows the for the non-edge and edge Pixel
values to be specified.
*Main> display . outline $ binaryStop
label :: (Image img, BinaryPixel (Pixel img)) => img -> GrayImage
Given a BinaryPixel
Image
, label
returns an Image
where Pixel
s in distinct connected components (based on 4-neighbor connectivity) have distinct integer values. These values range from 1 to n where n is the number of connected components in Image
.
*Main> display . makeHotImage . label $ binaryStop
distanceTransform :: (Image img, BinaryPixel (Pixel img)) => img -> GrayImage
Given a BinaryPixel
Image
, distanceTransform
returns an Image
representing the 2D distance transform of the Image
. The distance transform is accurate to within a 2% error for euclidean distance.
*Main> display . distanceTransform . dilate $ binaryStop
open :: (Eq (Pixel img), Num (Pixel img), Image img, BinaryPixel (Pixel img)) => \[\[Pixel img\]\] -> img -> img
Given a 2D list consisting solely of Pixel
s representing a structuring element, and a BinaryPixel
Image
, open
returns the morphological opening of the Image
with the structuring element. Note: There is a version open'
that uses the default structuring element [[1,1],[1,1]].
Main*> noise <- readColorImage "images/noise.ppm"
Main*> let noisyStop = binaryStop ./=. noise
Main*> display . open $ noisyStop
close :: (Eq (Pixel img), Num (Pixel img), Image img, BinaryPixel (Pixel img)) => \[\[Pixel img\]\] -> img -> img
Given a 2D list consisting solely of Pixel
s representing a structuring element, and a BinaryPixel
Image
, close
returns the morphological closing of the Image
with the structuring element. Note: There is a version close'
that uses the default structuring element [[1,1],[1,1]].
Main*>close [[1,1],[1,1]] noisyStop
areas :: (Image img, MaxMin (Pixel img), RealFrac (Pixel img)) => img -> V.Vector Double
Given an Image
, areas
returns a Vector
where the n-th component equals the number of Pixel
s with value n. If the Image
is the result of applying label to a BinaryPixel
Image
, then the Vector
represents the areas of the connected-components of the BinaryPixel
Image
. If not, areas returns the histogram of the Image
.
For example,
*Main> areas . label $ binaryStop
fromList [9240.0,1154.0,1326.0,809.0,1145.0]
perimeters :: (Image img, MaxMin (Pixel img), Pixel img ~ Double) => img -> V.Vector Double
Given an Image
, perimeters
returns a Vector
where the n-th component equals the number of Pixel
s with value n which are adjacent to Pixel
s of value 0 and the 0-th component equals the sum of the other components. If the Image
is the result of applying label to a BinaryPixel
Image
, then the Vector
represents the perimeters of the connected-components of the BinaryPixel
Image
.
For example,
*Main> perimeters . label $ binaryStop
fromList [1082.0,312.0,326.0,184.0,260.0]
centersOfMass :: (Image img, MaxMin (Pixel img), Pixel img ~ Double) => img -> [(Double, Double)]
Given an Image
, the result of applying label to a BinaryPixel
Image
, centersOfMass
returns a Vector
where the n-th component is a tuple representing the average row and column indices of Pixel
s of the n-th connected-component of the Image
.
For example,
*Main> centersOfMass . label $ binaryStop
[(42.2686308492201,24.657712305025996),(41.74660633484163,92.20889894419307),(35.31025957972806,57.595797280593324),(35.583406113537116,129.9170305676856)]
boundingBoxes :: (Image img, MaxMin (Pixel img), Pixel img ~ Double) => img -> [(Int, Int, Int, Int)]
Given an Image
, the result of applying label to a BinaryPixel
Image
, boundingBoxes
returns a Vector
where the n-th component is a four element tuple representing the minimum and maximum row and column indices of Pixel
s of the n-th connected-component of the Image
.
For example,
*Main> boundingBoxes . label $ binaryStop
[(10,8,73,41),(10,75,74,110),(11,42,72,73),(11,117,72,150)]