The paper discusses the pyramid methods of direct and inverse Q-transformation. Examples of method implementation based on numerical data transformation are considered. The work is dedicated to the development of a method of pyramid transformation based on contour Q-transformation for encoding and processing images. The method of pyramid Q-transformation and an example of its application are detailed, and the results of its software model are analyzed.
The article discusses the challenges of real-time data processing and analyzes various methods used to solve them, with a focus on image processing. It points out the limitations of existing methods and argues for the need to use more effective and modern technologies, proposing parallel-hierarchical networks as a promising solution. The article provides a detailed description of the structural-functional model of this type of network, which involves cyclically transforming the input data matrix using a "common part" criterion and an array evolution operator until a set of individual elements is formed. The proposed model is expected to improve real-time image recognition and can potentially be applied to other fields by using the "common part" criterion.
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