Pyramid Diffusion Models For Low-light Image Enhancement

05/17/2023
by   Dewei Zhou, et al.
0

Recovering noise-covered details from low-light images is challenging, and the results given by previous methods leave room for improvement. Recent diffusion models show realistic and detailed image generation through a sequence of denoising refinements and motivate us to introduce them to low-light image enhancement for recovering realistic details. However, we found two problems when doing this, i.e., 1) diffusion models keep constant resolution in one reverse process, which limits the speed; 2) diffusion models sometimes result in global degradation (e.g., RGB shift). To address the above problems, this paper proposes a Pyramid Diffusion model (PyDiff) for low-light image enhancement. PyDiff uses a novel pyramid diffusion method to perform sampling in a pyramid resolution style (i.e., progressively increasing resolution in one reverse process). Pyramid diffusion makes PyDiff much faster than vanilla diffusion models and introduces no performance degradation. Furthermore, PyDiff uses a global corrector to alleviate the global degradation that may occur in the reverse process, significantly improving the performance and making the training of diffusion models easier with little additional computational consumption. Extensive experiments on popular benchmarks show that PyDiff achieves superior performance and efficiency. Moreover, PyDiff can generalize well to unseen noise and illumination distributions.

READ FULL TEXT

page 1

page 3

page 4

page 6

research
07/27/2023

LLDiffusion: Learning Degradation Representations in Diffusion Models for Low-Light Image Enhancement

Current deep learning methods for low-light image enhancement (LLIE) typ...
research
07/05/2023

LLCaps: Learning to Illuminate Low-Light Capsule Endoscopy with Curved Wavelet Attention and Reverse Diffusion

Wireless capsule endoscopy (WCE) is a painless and non-invasive diagnost...
research
03/16/2023

Denoising Diffusion Post-Processing for Low-Light Image Enhancement

Low-light image enhancement (LLIE) techniques attempt to increase the vi...
research
08/13/2023

CLE Diffusion: Controllable Light Enhancement Diffusion Model

Low light enhancement has gained increasing importance with the rapid de...
research
06/25/2023

Diffusion Model Based Low-Light Image Enhancement for Space Satellite

Space-based visible camera is an important sensor for space situation aw...
research
08/18/2023

DiffLLE: Diffusion-guided Domain Calibration for Unsupervised Low-light Image Enhancement

Existing unsupervised low-light image enhancement methods lack enough ef...
research
07/15/2023

ExposureDiffusion: Learning to Expose for Low-light Image Enhancement

Previous raw image-based low-light image enhancement methods predominant...

Please sign up or login with your details

Forgot password? Click here to reset