Article ; Online: An Efficient Attentional Image Dehazing Deep Network Using Two Color Space (ADMC
2024 Volume 24, Issue 2
Abstract: Image dehazing has become a crucial prerequisite for most outdoor computer applications. The majority of existing dehazing models can achieve the haze removal problem. However, they fail to preserve colors and fine details. Addressing this problem, we ... ...
| Abstract | Image dehazing has become a crucial prerequisite for most outdoor computer applications. The majority of existing dehazing models can achieve the haze removal problem. However, they fail to preserve colors and fine details. Addressing this problem, we introduce a novel high-performing attention-based dehazing model (ADMC2-net)that successfully incorporates both RGB and HSV color spaces to maintain color properties. This model consists of two parallel densely connected sub-models (RGB and HSV) followed by a new efficient attention module. This attention module comprises pixel-attention and channel-attention mechanisms to get more haze-relevant features. Experimental results analyses can validate that our proposed model (ADMC2-net) can achieve superior results on synthetic and real-world datasets and outperform most of state-of-the-art methods. |
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| Language | English |
| Publishing date | 2024-01-22 |
| Publishing country | Switzerland |
| Document type | Journal Article |
| ZDB-ID | 2052857-7 |
| ISSN | 1424-8220 ; 1424-8220 |
| ISSN (online) | 1424-8220 |
| ISSN | 1424-8220 |
| DOI | 10.3390/s24020687 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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