The com.accusoft.imagegear.processing package API provides various image processing capabilities, including the following image correction, advanced image processing, and image effects methods:

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• Background Correction

  You can add, remove, or find the tilt for a specified image. These methods can be applied only to 8, 16 or 32-bpp grayscale images with one channel.

  Adding Tilt

  The ImGearRasterProcessing.AddTilt method adds a specified plane to the input image to correct for a tilt in the image luminance. The plane has X and Y zero crossing at the center of the input image with the slope of the plane in X direction and the slope of the plane in Y direction, as specified in the arguments.

  Removing Tilt

  The ImGearRasterProcessing.RemoveTilt method computes the best-fit plane for an image, and then subtracts that plane from the image to produce the output. This is very handy for correcting illumination gradients in a poorly digitized image.

  Finding Tilt The ImGearRasterProcessing.FindTilt Method computes the least-squares best fit plane for an image. The plane will be given by formula: f(x, y) = SlopeX * x + SlopeY * y + Piston.

• Bi-Linear and Bi-Cubic Interpolation

  ImageGear's implementation of bilinear and bicubic interpolation for image resize is designed for high image quality, especially when resizing large images down to small sizes (e.g., for thumbnail generation). Fine-tuning the sharpness of the resulting image can be done through the ImGearBilinearInterpolationOptions.setSharpness method and the ImGearBicubicInterpolationOptions.setSharpness method.

• Image Enhancement

  This ImGearRasterProcessing.EnhanceLocal method enhances sharpness of an image using the local standard deviation and mean.

  It transforms the input image f(x, y) to a new image g(x, y) based on the following formula,

  g(x, y) = A(x, y) * [f(x, y) - m(x, y)] + m(x, y)

  where,

  A(x, y) = k * M / sigma(x, y), with k being a scaling factor within the range [0, 1], m(x, y) and sigma(x, y) being the local mean and local standard deviation, and M being the global mean of the input image.

  To avoid the problem of spikes caused by too small local standard deviation, a check against the minimum allowed standard deviation is performed. If the local standard deviation is too small, the minimum allowed instead will be used in the calculation.

  Can be applied only to 8-bit grayscale images with one channel.

• Mathematical Morphology

• Speckle Removal

  • The ImGearRasterPage.Despeckle method removes the noise from a 1-bit image. For each pixel in the input image, it computes the average value of the neighboring pixels, and then uses the average value as the new value of that pixel in the output image. ImageGear allows you to specify the size of the neighborhood.
  • The ImGearRasterPage.GeomDespeckle method is used to reduce speckle noise from an image by using the Crimmins algorithm. It reduces the speckle index of an image by sending the image through a geometric filter, which uses the complementary hulling technique. The method has the effect of reducing the undesired speckle noise while preserving the edges of the original image. It can be applied only to 8-bit grayscale images with one channel.
• Gaussian Blur Effect

... and many more.

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