Adaptive Sampling for Storage of Progressive Images on DNA

2026-03-05

AI Summary

This work addresses the critical limitation of conventional DNA-based data storage—namely, the absence of an efficient random-access mechanism—which necessitates whole-pool sequencing for retrieving images at specific resolutions, resulting in prohibitive costs. To overcome this, the study introduces a novel integration of JPEG2000’s progressive coding with the JPEG DNA VM codec, enabling hierarchical encoding of images into DNA oligonucleotides according to resolution layers. Leveraging Oxford Nanopore’s adaptive sampling technology, the approach facilitates PCR-free, resolution-aware, on-demand readout by selectively sequencing only those oligonucleotides corresponding to the desired resolution. This targeted retrieval strategy dramatically reduces both sequencing volume and readout overhead, thereby enhancing the practicality and economic viability of DNA storage for image archiving.

Technology Category

Computer Vision: Image and Video RetrievalData Mining & Knowledge Management: Data CompressionSearch and Optimization: Distributed Search

Application Category

Security and Privacy: Data transparency and provenanceSearch and Retrieval-Augmented AI: Vertical and domain-specific searchResponsible Web: Data and user privacy-enhancing technologies for the Web

Abstract

The short lifespan of traditional data storage media, coupled with an exponential increase in storage demand, has made long-term archival a fundamental problem in the data storage industry and beyond. Consequently, researchers are looking for innovative media solutions that can store data over long time periods at a very low cost. DNA molecules, with their high density, long lifespan, and low energy needs, have emerged as a viable alternative to digital data archival. However, current DNA data storage technologies are facing challenges with respect to cost and reliability. Thus, coding rate and error robustness are critical to scale DNA storage and make it technologically and economically achievable. Moreover, the molecules of DNA that encode different files are often located in the same oligo pool. Without random access solutions at the oligo level, it is very impractical to decode a specific file from these mixed pools, as all oligos need to first be sequenced and decoded before a target file can be retrieved, which greatly deteriorates the read cost. This paper introduces a solution to efficiently encode and store images into DNA molecules, that aims at reducing the read cost necessary to retrieve a resolution-reduced version of an image. This image storage system is based on the Progressive Decoding Functionality of the JPEG2000 codec but can be adapted to any conventional progressive codec. Each resolution layer is encoded into a set of oligos using the JPEG DNA VM codec, a DNA-based coder that aims at retrieving a file with a high reliability. Depending on the desired resolution to be read, the set of oligos as well as the portion of the oligos to be sequenced and decoded are adjusted accordingly. These oligos will be selected at sequencing time, with the help of the adaptive sampling method provided by the Nanopore sequencers, making it a PCR-free random access solution.

Problem

• DNA data storage
• progressive image retrieval
• random access
• read cost
• oligo pool

Innovation

• adaptive sampling
• DNA data storage
• progressive image coding
• random access
• JPEG2000