A lossless compression method for random integer based on three-dimensional product- triangular chaotic iterative sequences. (1st April 2023) - Zhang, Qifan; Yu, Wanbo; Zhang, Qizhen
Abstract: Using the ergodicity of chaotic iterative sequences to realize data compression is a new research perspective. We find that, under suitable initial conditions, one or more local segments that are numerically identical to random integer sequences appear on the iterative sequence, which is a prerequisite for compression. Based on this, this paper designs a random integer lossless compression method based on three-dimensional product-triangular chaotic iterative sequences. The method proposed only needs to input a small amount of iterative initial information to compress a large amount of data through an iterative sequence of limited length. The key lies in three aspects. First, according to the characteristics of the data to be compressed, the iterative initial conditions suitable for compression are obtained by screening. Secondly, map the traversal results into a sequence of binary integers to complete the recording of key information. Finally, this binary integer sequence is rapidly compressed using a designed parity symmetric transformation algorithm, and decompression is achieved in its reverse process. As a new way to achieve compression, this approach is not only simple, but also requires less computation time. The experimental results show that the compression effect achieved by this method has obvious advantages in terms of compression ratio, data reconstruction quality, and compression and decompression speed.