A5063351753- Advanced Image Fusion Techniques
- Image Enhancement Techniques
- Advanced Image Processing Techniques
- Remote-Sensing Image Classification
- Image and Signal Denoising Methods
- Visual Attention and Saliency Detection
- Neural Networks and Applications
- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Color Science and Applications
Wuhan University
2022-2024
In this paper, we rethink the low-light image enhancement task and propose a physically explainable generative diffusion model for enhancement, termed as Diff-Retinex. We aim to integrate advantages of physical network. Furthermore, hope supplement even deduce information missing in through Therefore, Diff-Retinex formulates lowlight problem into Retinex decomposition conditional generation. decomposition, superiority attention Transformer meticulously design network (TDN) decompose...
Image fusion aims to combine information from different source images create a comprehensively representative image. Existing methods are typically helpless in dealing with degradations low-quality and non-interactive multiple subjective objective needs. To solve them, we introduce novel approach that leverages semantic text guidance image model for degradation-aware interactive task, termed as Text-IF. It innovatively extends the classical guided along ability harmoniously address...
In this paper, we rethink the low-light image enhancement task and propose a physically explainable generative diffusion model for enhancement, termed as Diff-Retinex. We aim to integrate advantages of physical network. Furthermore, hope supplement even deduce information missing in through Therefore, Diff-Retinex formulates problem into Retinex decomposition conditional generation. decomposition, superiority attention Transformer meticulously design network (TDN) decompose illumination...
In recent years, image segmentation based on deep learning has been widely used in medical imaging, automatic driving, monitoring and security. the fields of security, specific location a person is detected by segmentation, it segmented from background to analyze actions person. However, low-illumination conditions, great challenge traditional image-segmentation algorithms. Unfortunately, scene with low light or even no at night often encountered Given this background, paper proposes...
Low-light image enhancement aims at improving human perception or the effectiveness of computer vision tasks images taken in dark. The low-light are usually seriously lack visual information. To tackle this problem, we propose a general Image Enhancement Transformer Network (LLIEFormer) with degraded restoration model paper. network LLIEFormer synthesizes advantages to extract global information and convolutional neural networks capture local details. We conduct extensive experiments on...