Graphic filter library implemented in CUDA language

This thesis deals with the problem of reducing computation time of raster image processing by parallel computing on graphics processing unit. Raster image processing thereby refers to the application of graphic filters, which can be applied in sequence with different settings. This thesis evaluates the suitability of using parallelization on graphic card for raster image adjustments based on multicriterial choice. Filters are implemented for graphics processing unit in CUDA language. Opacity and image merging mode can be set for filters. Various types of filters were implemented like histogram, color, convolution filters and others. Within the frame of this thesis a graphic user interface was developed, which enables filter applying and setting for chosen image, measuring time needed for filter changes and saving final image