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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Publication Details

Journal
IEEE Transactions on NanoBioscience
Published
2025-02-21
DOI
https://doi.org/10.1109/tnb.2025.3544401
Citations
2
Primary Topic
Advanced Data Storage Technologies
Type
article
Field-Weighted Citation Impact
2.97

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article

High Fault-Tolerant DNA Image Storage System Based on VAE

Jing Yang, Zhihao Zhang, Cheng Zhang, Yuyang Lu
2 citations
IEEE Transactions on NanoBioscience
Advanced Data Storage Technologies
2.97
article

High Fault-Tolerant DNA Image Storage System Based on VAE

Jing Yang, Zhihao Zhang, Cheng Zhang, Yuyang Lu
article en
2 citations

Abstract

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.

IEEE Transactions on NanoBioscienceVol. 24(3)
North China Electric Power University (CN), Peking University (CN)
National Natural Science Foundation of China, Chinese Polar Environment Comprehensive Investigation and Assessment Programmes
Openalex Percentile: Top 10%
Advanced Data Storage Technologies
2.97
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