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We propose Deep Lossless Image Coding (DLIC), a full resolution learnedlossless image compression algorithm. Our algorithm is based on a neuralnetwork combined with an entropy encoder. The neural network performs a densityestimation on each pixel of the source image. The density estimation is thenused to code the target pixel, beating FLIF in terms of compression rate.Similar approaches have been attempted. However, long run times make themunfeasible for real world applications. We introduce a parallelized GPU basedimplementation, allowing for encoding and decoding of grayscale, 8-bit imagesin less than one second. Because DLIC uses a neural network to estimate theprobabilities used for the entropy coder, DLIC can be trained on domainspecific image data. We demonstrate this capability by adapting and trainingDLIC with Magnet Resonance Imaging (MRI) images.

Accelerated Deep Lossless Image Coding with Unified Paralleleized GPU Coding Architecture