Adaptive region algorithm based on a ternary optical computer

Abstract

The adaptive region algorithm is an improved compression algorithm based on Huffman coding. Because of the large number of rules for dividing regions in the algorithm, there are problems such as high computing costs, slow speed, and low compression efficiency. To address these problems, this paper investigates the adaptive region algorithm based on a ternary optical computer (TOC) combined with the characteristics of a ternary optical computer, such as many data bits, high parallelism, and three-valued coding. According to the characteristics of TOC three-valued coding, this paper designs a three-valued character coding scheme that can effectively shorten the coding length of characters by changing the original coding rules and further improve the compression efficiency of the adaptive region algorithm. Furthermore, in conjunction with the advantages of TOC enabling parallel computation, this paper presents an efficient computational scheme capable of effectively improving computational efficiency during the process of region partitioning. Through case studies, the compression efficiency and computational efficiency of the adaptive region algorithm implemented on TOC and an electronic computer were analyzed, respectively. It was found that the compression efficiency of the TOC-based algorithm is 50.4%, while that of the electronic-computer-based algorithm is only 36%. In the comparison of computational efficiency, the computational time complexity of TOC is O(n), whereas that of the electronic computer (EC) is O(n2). Finally, it is concluded through experimental validation that the TOC-based adaptive region compression algorithm performs well in terms of computational performance and compression efficiency, giving full play to the three-valued coding characteristics of TOC-based as well as the advantages of being able to realize parallel computation.