If you in Windows system, you can run DP-ID step by step.
The codes are located in the code folder, lena.bmp (256*256) is an example.The input image should be a 256*256 grayscale image. If it is other size or color image, please modify the corresponding parameters
Step 1 : run sanke_like.py to obtain the image matrix
step 2 : run dp-image_compression.cpp to achieve dp-compress
step 3 : run encode.py to convert the image matrix to bases
step 4 : simulate DNA storage errors. If you have simulator, please use it; otherwise, you can run simulation.py to simulate DNA storage errors
step 5 : run correct_length.py to correct DNA sequence to correct length
step 6 : run decode.py to convert bases to the image
If you in Linux system, you can run DP-ID in one step.
The codes are located in the linux folder, lena.bmp (256*256) is an example. The input image should be a 256*256 grayscale image. If it is other size or color image, please modify the corresponding parameters
Step : run dp_compress_inter.py to obtain the results
Xu, Q., Ma, Y., Lu, Z. Bi, K. DP-ID: Interleaving and Denoising to Improve the Quality of DNA Storage Image. Interdiscip Sci Comput Life Sci (2024). https://doi.org/10.1007/s12539-024-00671-6
If you have any questions, please contact corresponding author (bik@seu.edu.cn) and first author (xuqi@seu.edu.cn).
This project is licensed under the MIT License.