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CHANG Zhi-wen, WANG Li-zhong, LIANG Jin, LI Zhuang-zhuang, GONG Chun-yuan, WU Zhi-hui, XU Jian-ning. Underwater calibration image enhancement based on image block decomposition and fusion[J]. Chinese Optics. doi: 10.37188/CO.2023-0218
Citation: CHANG Zhi-wen, WANG Li-zhong, LIANG Jin, LI Zhuang-zhuang, GONG Chun-yuan, WU Zhi-hui, XU Jian-ning. Underwater calibration image enhancement based on image block decomposition and fusion[J]. Chinese Optics. doi: 10.37188/CO.2023-0218

Underwater calibration image enhancement based on image block decomposition and fusion

doi: 10.37188/CO.2023-0218
Funds:  Supported by the National Key R&D Program of China (No. 2022YFB4601802); National Natural Science Foundation of China (No. 52275543)
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  • Aiming at the loss of target point information caused by the degradation of underwater calibration images collected by camera calibration in underwater visual measurement, an underwater calibration image enhancement algorithm based on image block decomposition and fusion is proposed. First, given the difficulty of image dehazing caused by uneven illumination of underwater calibration images, image segmentation is implemented based on homomorphic filtering to calculate the global background light intensity and to achieve image dehazing. Then, given the problems such as noise, blur, and uneven illumination that still exist after the underwater image is dehazed, contrast enhancement and detail information enhancement are performed to obtain two complementary enhanced images. The complementary images are divided into multiple image blocks, and the image blocks are decomposed into three independent components, each of which is average intensity, signal intensity, and signal structure. The three components are separately fused and solved for the final enhanced image. Finally, subjective and objective evaluation and target point detection experiments are used to evaluate the enhanced quality of the underwater calibration image. Experimental results indicate that the visual effects and evaluation scores of the proposed are method higher than those of UDCP, MSR, and ACDC methods. When the turbidity is 7.6 NTU, 11.4 NTU, 15.7 NTU, and 18.4 NTU, the number of detected target points increases by 2.0%, 2.3%, 9.3%, and 21.2%. Therefore, we present a reliable and effective method to improve the quality of underwater calibration images and provides a stable and reliable underwater calibration image enhancement method for underwater visual measurement.


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