Formal analysis of 2D image processing filters using higher-order logic theorem proving

Abstract

AbstractTwo-dimensional (2D) image processing systems are concerned with the processing of the images represented as 2D arrays and are widely used in medicine, transportation and many other autonomous systems. The dynamics of these systems are generally modeled using 2D difference equations, which are mathematically analyzed using the 2D z-transform. It mainly involves a transformation of the difference equations-based models of these systems to their corresponding algebraic equations, mapping the 2D arrays (2D discrete-time signals) over the ($$z_1$$ z 1 ,$$z_2$$ z 2 )-domain. Finally, these ($$z_1$$ z 1 ,$$z_2$$ z 2 )-domain representations are used to analyze various properties of these systems, such as transfer function and stability. Conventional techniques, such as paper-and-pencil proof methods, and computer-based simulation techniques for analyzing these filters cannot assert the accuracy of the analysis due to their inherent limitations like human error proneness, limited computational resources and approximations of the mathematical expressions and results. In this paper, as a complimentary technique, we propose to use formal methods, higher-order logic (HOL) theorem proving, for formally analyzing the image processing filters. These methods can overcome the limitations of the conventional techniques and thus ascertain the accuracy of the analysis. In particular, we formalize the 2D z-transform based on the multivariate theories of calculus using the  theorem prover. Moreover, we formally analyze a generic ($$L_1,L_2$$ L 1 , L 2 )-order 2D infinite impulse response image processing filter. We illustrate the practical effectiveness of our proposed approach by formally analyzing a second-order image processing filter.