基于逻辑神经网络的图象处理方法

阐述了基于逻辑神经网络的图象平滑、压缩编码方法。这些方法的基本思想是：以逻辑神经网络为窗口,选择对某种图象变换敏感的模式训练窗口。当窗口对图象扫描时,窗口在图象的各位置输出响应,通过对这些响应的简单运算,实现所希望的处理。除了理论分析外,文中还给出了各种方法的典型试验结果。

METHODS OF IMAGE PROCESSING BASED ON LOGICAL NEURAL NETWORKS

Methods of image smoothing and compression based on logical neural networks are de-scribed.The basic idea of these methods is first to train networks using the patterns sensitive to certain image transformation,then to detect the responses of the networks to the patterns at cor-responding positions of the image in the process of the networks scanning across the image,to im-plement the desired transformation by the simple arithmetical operation of the responses. It is sim-ilar to the procedure of the adaptive pattern recognition in terms of the semi-transparent mapping from the pattern space into the response space instead of the classical mathematieal mapping.These methods,therefore,have the better self-adaptation,robustness,and the ability of massive parallel distributed processing,compared with the algorithm-based methods.In addition to theoretical analysis,typical experimental results are given.