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Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement
IEEE International Conference on Computer Vision, 2023When enhancing low-light images, many deep learning algorithms are based on the Retinex theory. However, the Retinex model does not consider the corruptions hidden in the dark or introduced by the light-up process.
Yuanhao Cai +5 more
semanticscholar +1 more source
SNR-Aware Low-light Image Enhancement
Computer Vision and Pattern Recognition, 2022This paper presents a new solution for low-light image enhancement by collectively exploiting Signal-to-Noise-Ratio-aware transformers and convolutional models to dynamically enhance pixels with spatial-varying operations.
Xiaogang Xu +3 more
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URetinex-Net: Retinex-based Deep Unfolding Network for Low-light Image Enhancement
Computer Vision and Pattern Recognition, 2022Retinex model-based methods have shown to be effective in layer-wise manipulation with well-designed priors for low-light image enhancement. However, the commonly used handcrafted priors and optimization-driven solutions lead to the absence of adaptivity
Wen-Bin Wu +5 more
semanticscholar +1 more source
Sparse Gradient Regularized Deep Retinex Network for Robust Low-Light Image Enhancement
IEEE Transactions on Image Processing, 2021Due to the absence of a desirable objective for low-light image enhancement, previous data-driven methods may provide undesirable enhanced results including amplified noise, degraded contrast and biased colors.
Wenhan Yang +4 more
semanticscholar +1 more source
Enhancing hyperspectral imaging
Nature Machine Intelligence, 2021Hyperspectral imaging can reveal important information without the need for staining. To extract information from this extensive data, however, new methods are needed that can interpret the spatial and spectral patterns present in the images.
Rohit Bhargava, Kianoush Falahkheirkhah
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Implicit Neural Representation for Cooperative Low-light Image Enhancement
IEEE International Conference on Computer Vision, 2023The following three factors restrict the application of existing low-light image enhancement methods: unpredictable brightness degradation and noise, inherent gap between metric-favorable and visual-friendly versions, and the limited paired training data.
Shuzhou Yang +4 more
semanticscholar +1 more source
American Journal of Roentgenology, 1983
A blurred mass subtraction technique has been developed for mammography that will enhance small object contrast and visibility throughout the breast area. The procedure is easy to implement and requires no additional exposure. Perception of low-contrast objects is improved by eliminating extreme light and dark image areas. Contrast of structures within
M B, McSweeney, P, Sprawls, R L, Egan
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A blurred mass subtraction technique has been developed for mammography that will enhance small object contrast and visibility throughout the breast area. The procedure is easy to implement and requires no additional exposure. Perception of low-contrast objects is improved by eliminating extreme light and dark image areas. Contrast of structures within
M B, McSweeney, P, Sprawls, R L, Egan
openaire +3 more sources
Image enhancement in ultrasound imaging
2016 24th Signal Processing and Communication Application Conference (SIU), 2016In this paper, two different methods are suggested in order to provide image enhancement in ultrasonic B-mode imaging. By obtaining RF data from two different phantom used to form B-mode image, their spectral characteristics were observed. Then by forming RF envelope from obtained data, conversion of envelope to color image is provided.
Tugba Ozge Onur, Rifat Hacioglu
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Global Structure-Aware Diffusion Process for Low-Light Image Enhancement
Neural Information Processing Systems, 2023This paper studies a diffusion-based framework to address the low-light image enhancement problem. To harness the capabilities of diffusion models, we delve into this intricate process and advocate for the regularization of its inherent ODE-trajectory ...
Jinhui Hou +5 more
semanticscholar +1 more source
2014 Twentieth National Conference on Communications (NCC), 2014
Image enhancement is a well established field in image processing. The main objective of image enhancement is to increase the perceptual information contained in an image for better representation using some intermediate steps, like, contrast enhancement, debluring, denoising etc.
Saumik Bhattacharya +2 more
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Image enhancement is a well established field in image processing. The main objective of image enhancement is to increase the perceptual information contained in an image for better representation using some intermediate steps, like, contrast enhancement, debluring, denoising etc.
Saumik Bhattacharya +2 more
openaire +1 more source