Hardware Implementation of a Desktop Supercomputer for High Performance Image Processing. Color Image Processing Using Cellular Neural Networks.

摘要

This report presents a software prototype capable of performing image processing applications using Cellular Neural Networks (CNN). The software is based on a CNN multi-layer structure in which each primary color is assigned to a unique layer. This allows an added flexibility as different processing applications can be performed in parallel. To be able to handle a full range of color tones, two novel color mapping schemes were derived. In the proposed schemes the color information is obtained from the cell's state rather than from its output. This modification is necessary because CNN has binary outputs from which only either a fully saturated or a black color can be obtained. Additionally, a post processor capable of performing pixelwise logical operations among color layers was developed to enhance the results obtained from CNN. Examples in the areas of medical image processing, image restoration and weather forecasting are provided to demonstrate the robustness of the software and the vast potential of CNN.