Efficient Constraining of Transcoding in DNA-Based Image Storage
Sara Al Sayyed, Aline Roumy, Thomas Maugey
TL;DR
This work tackles the challenge of storing data in DNA by balancing safety (homopolymer avoidance and GC content) with compression efficiency. It introduces two external transcoding schemes: Break-Sequence, which yields a variable rate but guarantees safety by preventing long homopolymers, and Tuned-Dictionary, which fixes the rate while allowing controlled safety via dictionary choices. The authors provide analytical rate-and-safety proofs (e.g., $R = (1- abla) \frac{1}{2} + \nabla$ with $\nabla = (1/4)^{K-2}$ and $K=4$, giving $R=0.53125$) and experimental validations showing BD-Rate improvements and zero or reduced homopolymer occurrences on JPEG-encoded images and a VVC video. The Break-Sequence method, in particular, achieves zero homopolymers with favorable rate, presenting a practical, low-complexity path to safe, efficient DNA-based storage for multimedia data.
Abstract
DNA has emerged as a promising alternative for long-term data storage due to its high capacity, durability, and low-energy potential. However, storing data in DNA presents several challenges. First, it requires complex and costly biochemical processes, making efficient compression crucial to reducing DNA synthesis time and cost. Second, these processes are prone to errors that must be avoided and/or corrected. In particular, homopolymers (repetitions of the same nucleotide) are a wellknown source of errors during the sequencing step. Avoiding such repetitions helps mitigate errors but introduces a constraint that may increase the data compression rate. In this paper, we propose two transcoding methods that address these two key challenges: reducing data rate and minimizing errors. The first method strictly enforces the error-minimization constraint by eliminating homopolymers of a certain length, at the cost of an increased data rate. In contrast, the second method accepts a slight increase in homopolymers. However, we show that these increases remain limited (2.14% increase in compression rate for the first method and 0.39% homopolymer rate for the second). These two approaches demonstrate that it is possible to efficiently constrain transcoding while balancing error minimization and compression performance.