This is the code repository of the following paper to train and perform inference with patch-based diffusion models for image restoration under adverse weather conditions."Restoring Vision in Adverse Weather Co
Özdenizci, O., Legenstein, R.: Restoring vision in adverse weather conditions with patch-based denoising diffusion models. IEEE Trans. Pattern Anal. Mach. Intell. 2023, 1 (2023) Google Scholar Zhao, C., Cai, W., Dong, C., Hu, C.: Wavelet-based Fourier information interaction with...
Notably, denoising diffusion probabilistic models (DDPMs) have shown great potential in text-to-image synthesis and have been adapted for image restoration tasks, including dehazing. However, current DDPM applications mainly use a patch-based approach and have not fully explored the benefits of ...
Tradi- tional pixel-based edge-preserving algorithms such as me- dian filters, bilateral filters [34], total variation [33] and anisotropic diffusion [33] have long served as workhorses in denoising tasks. These approaches focus on computing the (de)similarities between pixels within a local ...
a gold standard technique for core temperature measurement is required to calibrate the photoacoustic amplitude. Some noninvasive core temperature sensors based on thermal flux models suffer from slow response and lack of spatial resolution, which are not suitable for calibration in this case. Invasive...
Chen, G., Wu, Y., Shen, D., Yap, P.-T., 2016. XQ-NLM: denoising diffusion MRI data via x-q space non-local patch matching. In: Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI, pp. 587-595....
Denoising diffusion probabilistic models (DDPM) [37] are a class of generative models that have gained significant attention in recent years due to their ability to produce high-quality samples. DDPM consists of two main processes: the forward diffusion process and the denoising process. The ...
It is now common in image denoising field to utilize patch-based models and algorithms instead of pixel-based approaches to produce most promising estimate of the noise-free images. However, there are both advantages and disadvantages in the use of patch-based models and algorithms. There are se...
Dictionary-based denoising techniqueQuantitative evaluation of image qualityDiffusion-weighted imaging (DWI) is one of the most sensitive techniques to noise among magnetic resonance imaging (MRI) techniques. As the b-value used to acquire the DWI image increases, an image in which the difference in...
Chen, G., Wu, Y., Shen, D., Yap, P.-T., 2016. XQ-NLM: denoising diffusion MRI data via x-q space non-local patch matching. In: Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI, pp. 587-595....