Real-time image filtering: from optimal neuron evolution to vector quadratic programming

In this paper, a new scheme is introduced for the partitioning of images in image filtering using neural networks. The proposed scheme takes into account the physical nature of the image formation process, and thus simplifies the ordering scheme associated with the image processing framework based on neural networks with hierarchical cluster architecture. Also presented in the paper is a vector processing algorithm. By utilizing this algorithm, the pixels in the same row/column of an image are processed simultaneously. Compared with the scalar neuron evolution algorithms, the vector algorithm provides good visual quality in image filtering. Visual examples are provided to demonstrate the performance of the new approach