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Found 3 papers, 2 papers with code
Powerful Lossy Compression for Noisy Images
Image compression and denoising represent fundamental challenges in image processing with many real-world applications.
Make Lossy Compression Meaningful for Low-Light Images
Experimental results show that our proposed joint solution achieves a significant improvement over different combinations of existing state-of-the-art sequential ``Compress before Enhance'' or ``Enhance before Compress'' solutions for low-light images, which would make lossy low-light image compression more meaningful.
High-Fidelity Variable-Rate Image Compression via Invertible Activation Transformation
We implement the IAT in a mathematical invertible manner on a single rate Invertible Neural Network (INN) based model and the quality level (QLevel) would be fed into the IAT to generate scaling and bias tensors.
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