Similarity Enrichment in Image Compression through Weighted Finite Automata

Abstract

Abstract. We propose and study in details a similarity enrichment scheme for the application to the image compression through the extension of the weighted finite automata (WFA). We then develop a mechanism with which rich families of legitimate similarity images can be systematically created so as to reduce the overall WFA size, leading to an eventual better WFA-based compression performance. A number of desirable properties, including WFA of minimum states, have been established for a class of packed WFA. Moreover, a codec based on a special extended WFA is implemented to exemplify explicitly the performance gain due to extended WFA under otherwise the same conditions.

Weighted automata and weighted logics with discounting

“…Theorem 29); we will also obtain equivalence to weighted Muller automata; (3) show that for the class of additively locally finite semirings, a purely syntactically defined fragment of the weighted logic suffices to achieve the equivalences of (1) and (2) (cf. Theorem 11(b) and 29).…”

“…Both of these results have led to various extensions and also to practical applications, e.g. in verification of finite state programs [1,37,41], in digital image compression [8,[28][29][30] and in speech-to-text processing [5,32,43]. For surveys and monographs on weighted automata see [3,14,34,36,46].…”

Weighted Automata and Weighted Logics

“…[24,21,15,2] for surveys and monographs, and also led to recent practical applications, e.g. in verification of finite-state programs (model checking, [17,1,16]), in digital image compression [5,11,13,12] and in speech-to-text processing [19,20,4].…”

Extending Parikh’s Theorem to Weighted and Probabilistic Context-Free Grammars

“…Since the seminal paper of Schützerberger [31], weighted automata have inspired a wealth of extensions and further research (see [9] for a recent handbook compilation). Weighted automata have found applications in verification [8,4,5,23], reasoning about competitive ratio of online algorithms [1], digital image compression [6,15,20,21], in speech-to-text processing [24,25,3], and data flow analysis [30,29]. A special case of weighted automata are probabilistic automata [28,27] that model randomized algorithms and stochastic uncertainties in the system environment.…”