Perception-based Image Denoising via Generative Compression

1. 1Implement a generative compression framework using entropy-coded latent representations
2. 2Configure the framework to enforce low-complexity structure in the reconstructed images
3. 3Test the framework on various noisy images to evaluate its performance
4. 4Apply the framework to real-world applications, such as image restoration and enhancement
5. 5Evaluate the results using perceptual metrics, such as PSNR and SSIM
6. 6Optimize the framework for better performance and efficiency

Computer vision engineers and researchers on a team can benefit from this technique to improve image denoising capabilities, and software engineers can implement this framework in various applications

💡 Generative compression can be used for perception-based image denoising by reconstructing from entropy-coded latent representations that enforce low-complexity structure

💡 Perception-based image denoising via generative compression! Improve image quality while preserving structural details and realism