Uses of Class
net.grelf.grip.ImageDouble

Packages that use ImageDouble
net.grelf.grip This package contains the Java classes which are specific to the image processing application GRIP.

GRIP is available as a free download from www.grelf.net - please always quote this URL in connection with GRIP.
Version: 11.11.21 
 

Uses of ImageDouble in net.grelf.grip
 

Subclasses of ImageDouble in net.grelf.grip
 class AccumulatorDouble
          This is a 64-bits-per-channel floating point Accumulator.
 

Methods in net.grelf.grip that return ImageDouble
static ImageDouble Convolutions.blurGaussian(ImageDouble srcAccum, int nx, int ny)
          Do Gaussian blurring of the given image with 1D profiles of width nx (horizontal) and ny (vertical) and return the quite separate resulting new image.
 ImageDouble ImageInt.convertToAccumulatorDouble()
          Convert to an AccumulatorDouble containing the same values.
static ImageDouble Convolutions.convolve(ImageDouble srcAccum)
          Convolve the given image with the current kernel and return the quite separate resulting new image.
static ImageDouble Convolutions.convolve1D(ImageDouble srcAccum, double[] horz, double[] vert)
          Convolve the given image with the given 1D arrays (horizontal and vertical - may be different) and return the quite separate resulting new image.
static ImageDouble Convolutions.deconvolve(ImageDouble originalAccum, ImageDouble srcAccum, int passNo)
          Deconvolve the image with the current kernel, using van Cittert's method.
 

Methods in net.grelf.grip with parameters of type ImageDouble
 void ImageDouble.add(ImageDouble other)
          Add pixel values from another Image into the data array.
 void ImageDouble.add(ImageDouble other, double f1, double f2)
          Add pixel values from another Image into the data array, taking fraction f1 of the values in the current Image and f2 of those in the other.
static ImageDouble Convolutions.blurGaussian(ImageDouble srcAccum, int nx, int ny)
          Do Gaussian blurring of the given image with 1D profiles of width nx (horizontal) and ny (vertical) and return the quite separate resulting new image.
static ImageDouble Convolutions.convolve(ImageDouble srcAccum)
          Convolve the given image with the current kernel and return the quite separate resulting new image.
static ImageDouble Convolutions.convolve1D(ImageDouble srcAccum, double[] horz, double[] vert)
          Convolve the given image with the given 1D arrays (horizontal and vertical - may be different) and return the quite separate resulting new image.
static ImageDouble Convolutions.deconvolve(ImageDouble originalAccum, ImageDouble srcAccum, int passNo)
          Deconvolve the image with the current kernel, using van Cittert's method.
 void ImageDouble.multiply(ImageDouble other)
           
 void ImageDouble.multiply(ImageDouble other, double f1, double f2)
          Multiply fraction f1 of this accumulator by f2 of the other.
static byte[][] StarSegmenter.segment(ImageDouble accum, int difference, int radius)
          Segment the image to detect pixels in stars using the given parameters.
 void ImageDouble.subtract(ImageDouble other)
          Subtract other from this, pixel by pixel, the result being about the half-way brightness level so that both negative and positive results can be seen.
 void ImageDouble.subtractToZero(ImageDouble other)
          Subtract other from this, pixel by pixel, negative results being cut off at zero.