Image restoration by a neural network with hierarchical clustered architecture
Ling Guan · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
This paper proposes a novel image restoration approach by a neural network with hierarchical clustered architecture (NNHCA). The method is motivated by a universally accepted concept in digital image processing that natural image formation is a local process, and treats image restoration also as a globally coordinated local process. The image restoration based on the local model is realized by NNHCA, one of the recently emerged neural networks with sophisticated architectures. In the application of restoration, NNHCA consists of four processing levels. The zeroth level represents individual processing units. The first level simulates optimization process which governs local restoration. The second level acts as a link for information exchange between local clusters in the first level. And the third level coordinates the completes process.