水下
人工智能
计算机视觉
计算机科学
图像复原
对比度(视觉)
颜色校正
图像融合
图像增强
频道(广播)
图像(数学)
噪音(视频)
对比度增强
图像质量
图像处理
地质学
医学
计算机网络
海洋学
磁共振成像
放射科
标识
DOI:10.1142/s0218001420540075
摘要
Optical properties of water distort the quality of underwater images. Underwater images are characterized by poor contrast, color cast, noise and haze. These images need to be pre-processed so as to get some information. In this paper, a novel technique named Fusion of Underwater Image Enhancement and Restoration (FUIER) has been proposed which enhances as well as restores underwater images with a target to act on all major issues in underwater images, i.e. color cast removal, contrast enhancement and dehazing. It generates two versions of the single input image and these two versions are fused using Laplacian pyramid-based fusion to get the enhanced image. The proposed method works efficiently for all types of underwater images captured in different conditions (turbidity, depth, salinity, etc.). Results obtained using the proposed method are better than those for state-of-the-art methods.
科研通智能强力驱动
Strongly Powered by AbleSci AI