A Wavelet-based Image Coding Framework for Data Storage on DNA

In the face of the exponential growth of digital data, DNA is expected to become a new storage medium. Image data makes up a large proportion of digital data. However, existing DNA data storage models are mainly designed for general files. To address this issue, we propose a novel image encoding method for DNA data storage. We employ discrete wavelet transform to decompose the image and utilize an improved exponent-mantissa representation for numerical data. Subsequently, we achieve enhanced compression performance through context-adaptive arithmetic coding. Additionally, we construct a dictionary between ternary sequences and oligonucleotides to generate nucleotide sequences that meet the specified constraints. Experiments show that our method outperforms JPEG-DNA and BioCoder in compression performance and generates higher-quality nucleotide sequences.