Cycle-dehaze
时间: 2023-09-29 13:10:05 浏览: 62
Cycle-Dehaze是一种增强版的CycleGAN架构,用于单图像去雾。与CycleGAN相比,Cycle-Dehaze引入了一个额外的损失函数,即循环感知一致性损失。其目标是通过优化CycleGAN架构并增加循环感知一致性损失来实现去雾效果。在测试时,Cycle-Dehaze使用生成器G*来获得无雾的图像。
Cycle-Dehaze的网络结构借鉴了EnhanceNet的感知损失思想,将原始图像与重建的循环图像在特征空间进行比较,而不是在像素空间进行比较。循环一致性损失确保高峰值信噪比(PSNR),而感知损失在特征空间保持图像的清晰度。此外,Cycle-Dehaze还使用传统的拉普拉斯金字塔在主要去雾过程之后提供更好的上采样结果。
文献提出了Cycle-Dehaze的增强版CycleGAN,该论文的标题是《Cycle-Dehaze: Enhanced CycleGAN for Single Image Dehazing》,作者是Deniz Engin、Anil Genç和Hazim Kemal Ekenel。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* [Cycle-Dehaze: Enhanced CycleGAN for Single Image Dehazing循环去雾:增强循环gan单幅图像去雾(重要基础...](https://blog.csdn.net/m0_75262530/article/details/131486884)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_1"}}] [.reference_item style="max-width: 33.333333333333336%"]
- *2* [Cycle-Dehaze:用于单图像去雾的增强型 CycleGAN(2018_CVPR)](https://blog.csdn.net/weixin_44021553/article/details/124333731)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_1"}}] [.reference_item style="max-width: 33.333333333333336%"]
- *3* [细节增强的matlab代码-Cycle-Dehaze:循环除雾](https://download.csdn.net/download/weixin_38617335/19109106)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_1"}}] [.reference_item style="max-width: 33.333333333333336%"]
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