Resampling Methods (Especially for GATE-Geospatial 2022)

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The three techniques for determining output values are:

  • Nearest neighbor
  • Bilinear interpolation
  • Cubic convolution

Nearest Neighbor

Nearest neighbor resampling method fills each pixel of the new image with the nearest pixel value from the original image.

To determine the nearest neighbor, the algorithm uses the inverse of the transformation matrix to calculate the image file coordinates of the desired geographic coordinate.

The pixel value occupying the closest image file coordinate to the estimated coordinate will be used for the output pixel value in the georeferenced image.

Image Shows the Pixel Value Occupying the Closest Image File …

Nearest Neighbor Resampling

This Image Shows Nearest Neighbor Resampling

Bilinear Interpolation

Bilinear interpolation uses the value of the four nearest input cell centers to determine the value on the output raster. The new value for the output cell is a weighted average of these four values, adjusted to account for their distance from the center of the output cell in the input raster. This interpolation method results in a smoother-looking surface than can be obtained using nearest neighbor.

Bilinear Interpolation Resampling

This Image Shows Bilinear Interpolation Resampling

Cubic Convolution

The weighted average is calculated from the 16 nearest input cell centers and their values.

The output is similar to bilinear interpolation, but the smoothing effect caused by the averaging of surrounding input pixel values is more dramatic.

Cubic convolution will have a tendency to sharpen the data more than bilinear interpolation since more cells are involved in the calculation of the output value.

Cubic Convolution Resampling

This Image Shows Cubic Convolution Resampling

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