A Underwater Sequence Image Dataset for Sharpness and Color Analysis

• Main Authors: Dong, J. (Author), Wang, H. (Author), Xie, Z. (Author), Yang, M. (Author), Yin, G. (Author), Zheng, B. (Author)
• Format: Article
• Language: English
• Published: MDPI 2022
• Subjects: Color; Color analysis; Color distortions; Image analysis; Image datasets; Image enhancement; Image quality; Image quality assessment; Imaging systems; Plane target; Quality control; Quality degradation; sequence image; Sequence images; underwater dataset; Underwater dataset; Underwater environments; underwater image quality; Underwater image quality; Underwater imaging
• Online Access: View Fulltext in Publisher

 The complex underwater environment usually leads to the problem of quality degradation in underwater images, and the distortion of sharpness and color are the main factors to the quality of underwater images. The paper discloses an underwater sequence image dataset called TankImage-I with gradually changing sharpness and color distortion collected in a pool. TankImage-I contains two plane targets, a total of 78 images. It includes two lighting conditions and three different water transparency. The imaging distance is also changed during the photographing process. The paper introduces the relevant details of the photographing process, and provides the measurement results of the sharpness and color distortion of the sequence images. In addition, we verify the performance of 13 image quality assessment methods on TankImage-I, and analyze the results of 13 image quality assessment methods from the aspects of sharpness and color, which provides a reference for the design and improvement of underwater image quality assessment algorithm and underwater imaging system design. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.