Applying OLAP Pre-Aggregation Techniques to ... - Jacobs University

56 3. Fundamental Geo-Raster Operations
(a) Original domain
(b) Translated domain
Figure 3.19. Computation of a Translation Operation for a Raster Image
where (x 0 , y 0 ) are the coordinates of the center of rotation in the input raster image,
and θ is the angle of rotation. Existing algorithms for the computation of rotation,
unlike those employed by translation, can produce coordinates (x 2 , y 2 ) that are not
integers. A common solution to this problem is the application of interpolation techniques
like nearest neighbor, bilinear, or cubic interpolation. For large raster datasets
this is an intensive computing problem because every output cell must be computed
separately using data from its neighbors. Consequently, the rotation operation is not
yet properly supported by Array Algebra.
Scaling
Scaling stretches or compresses the coordinates of a raster (or part of it) according
to a scaling factor. This operation can be used to change the visual appearance of an
image, to alter the quantity of information stored in a scene representation, or as a lowlevel
preprocessor in a multi-stage image processing chain that operates on features of
a particular scale. For the estimation of the cell values in a scaled output raster image,
two common approaches exist:
• one pixel value within a local neighborhood is chosen (perhaps randomly) to
be representative of its surroundings. This method is computationally simple
but may lead to poor results when the sampling neighborhood is too large and
diverse.
• the second method interpolates cell values within a neighborhood by taking the
average of the local intensity values.