基于 VAE 的高容错 DNA 图像存储系统。

IF 4.4 4区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Yuyang Lu;Zhihao Zhang;Jing Yang;Cheng Zhang
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引用次数: 0

摘要

基于dna的存储由于其巨大的存储潜力而成为一种有前途的存储范式。然而,DNA测序和合成过程容易出错的性质限制了这种潜力。图像数据通常在存储之前进行压缩,即使是单个不匹配也可能导致在解压缩期间灾难性的错误传播,从而使图像无法恢复。为了降低基于DNA存储的图像压缩的错误率,我们设计了一个高容错性的DNA图像存储系统,并将其应用于DNA存储的图像压缩中。该系统通过三个关键创新实现了图像数据压缩比和弹性的显著提高:1)使用变分自编码器(VAE)将图像压缩成均匀大小的潜在变量块,然后通过奇异值分解(SVD)进一步压缩;2)对潜变量块中的浮点数进行量化,并对得到的三元序列进行旋转编码,有效地保证了对均聚物运行长度和GC含量的正约束;3)优化纠错方案,将每一类误差量化回原值,使其得到最佳恢复。通过图像缩放调整压缩比,图像压缩仿真对比结果验证了该模型的性能,突出了其在容错性和存储密度方面的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High Fault-Tolerant DNA Image Storage System Based on VAE
DNA-based storage has emerged as a promising storage paradigm due to its immense storage potential. However, the error-prone nature of DNA sequencing and synthesis processes limits this potential. Image data is typically compressed before storage, and even a single mismatch can lead to catastrophic error propagation during decompression, rendering the image unrecoverable. To reduce the error rate of DNA storage-based image compression, we have designed a high fault-tolerant DNA image storage system and applied it to image compression for DNA storage. This system achieves significant improvements in both image data compression ratio and resilience through three key innovations: 1) Using a Variational Autoencoder (VAE) to compress the image into uniformly sized latent variable blocks, followed by further compression via Singular Value Decomposition (SVD); 2) Quantizing the floating-point numbers in the latent variable blocks and applying rotational coding to the resulting ternary sequences, effectively ensuring positive constraints on homopolymer run lengths and GC content; 3) Optimizing the error-correction scheme to best recover each type of error by quantizing it back to its original value. Through image scaling, we adjust the compression ratio, and the comparative results of image compression simulations demonstrate the performance of the proposed model, highlighting its superiority in fault tolerance and storage density.
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来源期刊
IEEE Transactions on NanoBioscience
IEEE Transactions on NanoBioscience 工程技术-纳米科技
CiteScore
7.00
自引率
5.10%
发文量
197
审稿时长
>12 weeks
期刊介绍: The IEEE Transactions on NanoBioscience reports on original, innovative and interdisciplinary work on all aspects of molecular systems, cellular systems, and tissues (including molecular electronics). Topics covered in the journal focus on a broad spectrum of aspects, both on foundations and on applications. Specifically, methods and techniques, experimental aspects, design and implementation, instrumentation and laboratory equipment, clinical aspects, hardware and software data acquisition and analysis and computer based modelling are covered (based on traditional or high performance computing - parallel computers or computer networks).
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