Abstract
Images captured from underwater environment always suffer from color distortion, detail loss, and contrast reduction due to the medium scattering and absorption. This paper introduces an enhancement approach to improve the visual quality of underwater images, which does not require any dedicated devices or additional information more than the native single image. The proposed strategy consists of two steps: an improved white-balancing approach and an artificial multiple underexposure image fusion strategy for underwater imaging. In our white-balancing approach, the optimal color-compensated approach is determined by the sum of the Underwater Color Image Quality Evaluation (UCIQE) and the Underwater Image Quality Measure (UIQM). We get an optimal white-balanced version of the input by combining the well-known Gray World assumption and the optimal channel-compensated approach. In our artificial multiple underexposure image fusion strategy, first the gamma-correction operation is adopted to generate multiple underexposure versions. Then we propose to use ‘contrast’, ‘saturation’, and ‘well-exposedness’ as three weights, to be blended into the well-known multi-scale fusing scheme. Images enhanced by our strategy have a better visual quality than some state-of-the-art underwater dehazing techniques, through our validation with a wide range of qualitative and quantitative evaluations.
Highlights
The utilization and exploitation of various marine creatures and resources have been a hot-issue recently
In order to verify the effectiveness of our white-balancing method, we first employed some images with different degrees of degradation from the RUIE database [67], to compare our whitebalancing method with different white-balancing methods (Gray Edge [50], Max RGB [52], Shades of Gray [51], Gray World [21], Ancuti et al [47] and Ancuti et al [48])
This paper introduced an enhancement approach to clarify underwater single image
Summary
The utilization and exploitation of various marine creatures and resources have been a hot-issue recently. Besides photography and video recording, underwater imaging has been applied to various work tasks and scientific discoveries, such as underwater artificial-facility monitoring [1], underwater object detection [2], marine creatures discovering [3], and underwater vehicles controlling [4]. Numerous approaches have been proposed to improve the visibility of underwater images. Some researchers proposed to use the dedicated hardware devices [11], [12], or polarization-based methods [13], [14] to enhance degraded images. Even though the performance by using these methods was excellent, limitations still existed These methods were limited by extremely expensive hardware devices, or were not applicable to video acquisitions and dynamic imaging occasions. Some researchers proposed to employ multi-images-based fusion techniques[15], [16] to improve the visual quality of the scenario. The extremely difficult operation that acquiring multiple-versions of one scene in underwater imaging is impractical for common users
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