(untitled) (International Journal of Advanced Research in Computer Science, 2017)
This paper presents a raster simulator software capable of performing Image Processing applications using Cellular Neural Network (CNN). The CNN paradigm has rapidly evolved to cover a wide range of applications. The basic structure simulator is based on high â€“ performance software capable of efficiently dealing with large images in the order of 105 pixels. The simulator operates in sequential mode. This provides an added flexibility to create individual templates that can be applied on single color layer to obtain full mix of colors. To perform any kind of color image processing, a color model is selected. Two color mapping schemes are used that effectively assign states to distinct color hues. Image processing with CNN may not always yield the desired visual results and post processing becomes necessary to enhance the visualization of the image. The simulator runs in an X-windows environment and uses standard graphics format as input. Â Keywords: Cellular Neural Networks, X â€“ Windows environment, Color Mapping, Raster simulator, Visualization.