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To use these functions, the ImageJCV Feature is required.

convertCV(ImageCV i, Number newPixelFormat)

Converts the input image to another pixel format.

Example
output = MAP({expressions=[['convertCV(image, 28)', 'converted']]}, input)

getWidthCV(ImageCV i)

Returns the width of the given image

Example
output = MAP({expressions=[['getWidth(image)', 'width']]}, input)

getHeightCV(ImageCV i)

Returns the height of the given image

Example
output = MAP({expressions=[['getHeight(image)', 'height']]}, input)

getDepthCV(ImageCV i)

Returns the depth of the given image

Example
output = MAP({expressions=[['getDepth(image)', 'depth']]}, input)

getNumChannelsCV(ImageCV i)

Returns the number of channels of the given image 

Example
output = MAP({expressions=[['getNumChannels(image)', 'numChannels']]}, input)

getPixelFormatCV(ImageCV i)

Returns the pixel format of the given image

Example
output = MAP({expressions=[['getPixelFormat(image)', 'pixelFormat']]}, input)

resizeCV(ImageCV i, Number width, Number height)

Resizes the image to the given width and height

Example
output = MAP({expressions=[['resizeCV(image, 100, 100)', 'smallImage']]}, input)

stretchContrastCV(ImageJCV i, Number oldMin, Number oldMax, Number newMin, Number newMax)

Converts an 16-bit 1-channel image (f.ex. a temperature map) to an 24-bit RGB grayscale image. The contrast of the new image is calculated with this formula for each pixel:

newValue = (oldValue - oldMin) / (oldMax - oldMin) * (newMax - newMin) + newMin

The example converts a temperature map to a grayscale image such that input 1000 maps to black and input 5000 maps to white.

Example
output = MAP({expressions=[['stretchContrastCV(image, 1000, 5000, 0, 255)', 'grayscale']]}, input)

toImageCV(Number width, Number height)

Creates a new 32-bpp RGBA image with the given width and height

Example
output = MAP({expressions=[['toImageCV(512, 512)', 'image']]}, input)

toImageCV(Number width, Number height, Number depth, Number numChannels, Number pixelFormat)

Creates a new image with the given width, height, depth, channel count and pixel format.

Example
output = MAP({expressions=[['toImageCV(512, 512, 8, 4, 28)', 'image']]}, input) /// 32bpp RGBA image

toImageCV(Image i)

Copies the contents of the input image (from the Image feature) into a new ImageJCV image.

Example
output = MAP({expressions=[['toImageCV(inputImage)', 'image']]}, input)

reinterpretCV(ImageJCV i, Number newWidth, Number newHeight, Number newDepth, Number newNumChannels, Number newPixelFormat)

Reinterprets the content of an image (argument 0) as another image with different width, height, depth, number of channels or pixel format. Any parameter which is set to 1 will be replaced by the corresponding value of the original image. Buffer sizes of original and reinterpreted image must match!

Example: Convert a 16-bit grayscale image to a 32-bit RGBA image with half of the width:

Example
output = MAP({expressions=[['reinterpret(image, getWidth(image)/2, -1, 8, 4, 28)', 'image']]}, input)

Parameter explanation:

  • image: Original image
  • getWidth(image)/2: Half width
  • -1: Original height
  • 8: 8 bit per pixel channel
  • 4: 4 channels per pixel
  • 28: 32 Bit RGBA pixel format

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