.png){kind=icon}
返回
Saturated Reflection Detection for Reflection Removal Based on Convolutional Neural Network
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2022.3166186.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Single image reflection removal is a technique that removes undesirable reflections, which occur due to glass, from images. Various methods of reflection removal have been proposed, but unfortunately, they usually fail to remove reflections particularly with very high pixel values. In this paper, we define these saturated reflections and their characteristics, as well as discuss and propose a removal system. The proposed system detects areas of saturated reflections based on our proposed model of convolutional neural networks and restores them by a conventional method of image estimation. In our experiments, the proposed system shows better peak-signal-to-noise ratio scores and perceptual quality than conventional methods of reflection removal.
Keyword:
Convolutional neural networks
Glass
Light sources
Estimation
Convolution
Licenses
Laplace equations
Single image reflection removal
reflection detection
convolutional neural network
image inpainting
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
.png){kind=icon}
Generation of hydroxyl radicals by urban suspended particulate air matter. The role of iron ions城市悬浮颗粒物产生羟基自由基。铁离子的作用:
PREAI
分享收藏Geospatial Assessment of Urban Growth Dynamics and Land Surface Temperature in Ajmer Region, India
PREAI
分享收藏
查看更多内容