Abstract
Texture-based visualization method is a common method in the visualization of vector field data. Aiming at adding color mapping to the texture of ocean vector field and solving the ambiguity of vector direction in texture image, a new color texture enhancement algorithm based on the Line Integral Convolution (LIC) for the vector field data is proposed, which combines the HSV color mapping and cumulative distribution function calculation of vector field data. This algorithm can be summarized as follows: firstly, the vector field data is convoluted twice by line integration to get the gray texture image. Secondly, the method of mapping vector data to each component of the HSV color space is established. And then, the vector field data is mapped into HSV color space and converted from HSV to RGB values to get the color image. Thirdly, the cumulative distribution function of the RGB color components of the gray texture image and the color image is constructed to enhance the gray texture and RGB color values. Finally, both the gray texture image and the color image are fused to get the color texture. The experimental results show that the proposed LIC color texture enhancement algorithm is capable of generating a better display of vector field data. Furthermore, the ambiguity of vector direction in the texture images is solved and the direction information of the vector field is expressed more accurately.
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Acknowledgements
We thank the State Key Laboratory of Computer Aided Design and Computer Graphics (CAD&CG), Zhejiang University and Dalian Naval Academy for providing some vector field data such as ocean wind field and ocean current.
Funding
The National Natural Science Foundation of China under contract Nos 61702455, 61672462 and 61902350; the Natural Science Foundation of Zhejiang Province, China under contract No. LY20F020025.
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Zheng, H., Shao, Q., Chen, J. et al. LIC color texture enhancement algorithm for ocean vector field data based on HSV color mapping and cumulative distribution function. Acta Oceanol. Sin. 41, 171–180 (2022). https://doi.org/10.1007/s13131-022-2020-6
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DOI: https://doi.org/10.1007/s13131-022-2020-6