Abstract
Photographic volumes keep the original color in each voxel, and play an important role in medical and biological researches. The gradient is one of the most widely used attributes in volume visualization. However, it is more difficult to accurately estimate gradients for photographic volumes than scalar volumes. Current gradient estimators for photographic volumes do not work well for all cases, especially when the data is noisy. In this paper, we propose a new method to estimate gradients accurately and robustly for photographic volumes. Colors are directly used for gradient estimation instead of being converted to grayscale values, to ensure the accuracy of the gradient direction. For each of three gradient components in x, y and z directions, different filters are combined to reduce the negative effect of noises and generate an accurate result. Experiment results show that the proposed method can estimate gradients robustly in the presence of noise and outperforms other gradient estimators in photographic volume visualization.
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References
Correa, C., Hero, R., Ma, K.-L.: A comparison of gradient estimation methods for volume rendering on unstructured meshes. IEEE Trans. Vis. Comput. Graph. 17(3), 305–319 (2011)
Ebert, D.S., Morris, C.J., Rheingans, P., Yoo, T.S.: Designing effective transfer functions for volume rendering from photographic volumes. IEEE Trans. Vis. Comput. Graph. 8(2), 183–197 (2002)
Ercan, G., Whyte, P.: Digital image processing. US Patent 6,240,217 29 May 2001
Evans, A.N., Liu, X.U.: A morphological gradient approach to color edge detection. IEEE Trans. Image Process. 15(6), 1454–1463 (2006)
Gargesha, M., Qutaish, M., Roy, D., Steyer, G., Bartsch, H., Wilson, D.L.: Enhanced volume rendering techniques for high-resolution color cryo-imaging data. In: SPIE Medical Imaging, p. 72622V. International Society for Optics and Photonics (2009)
Kindlmann, G., Durkin, J.W.: Semi-automatic generation of transfer functions for direct volume rendering. In: Proceedings of the 1998 IEEE Symposium on Volume Visualization, pp. 79–86. ACM (998)
Kniss, J., Premoze, S., Hansen, C., Shirley, P., McPherson, A.: A model for volume lighting and modeling. IEEE Trans. Vis. Comput. Graph. 9(2), 150–162 (2003)
Levoy, M.: Display of surfaces from volume data. IEEE Comput. Graph. Appl. 8(3), 29–37 (1988)
Max, N.: Optical models for direct volume rendering. IEEE Trans. Vis. Comput. Graph. 1(2), 99–108 (1995)
Morris, C.J., Ebert, D.: Direct volume rendering of photographic volumes using multi-dimensional color-based transfer functions. In: Proceedings of the Symposium on Data Visualisation 2002, pp. 115-ff. Eurographics Association (2002)
Nezhadarya, E., Ward, R.K.: A new scheme for robust gradient vector estimation in color images. IEEE Trans. Image Process. 20(8), 2211–2220 (2011)
Pfister, H., Lorensen, B., Bajaj, C., Kindlmann, G., Schroeder, W., Avila, L.S., Raghu, K., Machiraju, R., Lee, J.: The transfer function bake-off. IEEE Comput. Graph. Appl. 21(3), 16–22 (2001)
Plataniotis, K.N., Venetsanopoulos, A.N.: Color Image Processing and Applications: Digital Signal Processing. Springer, Heidelberg (2000)
Roettger, S., Bauer, M., Stamminger, M.: Spatialized transfer functions. In: Proceedings of the Seventh Joint Eurographics/IEEE VGTC Conference on Visualization, pp. 271–278. Eurographics Association (2005)
Roy, D., Steyer, G.J., Gargesha, M., Stone, M.E., Wilson, D.L.: 3D cryo-imaging: a very high-resolution view of the whole mouse. Anat. Rec. 292(3), 342–351 (2009)
Russo, F., Lazzari, A.: Color edge detection in presence of Gaussian noise using nonlinear prefiltering. IEEE Trans. Instrum. Meas. 54(1), 352–358 (2005)
Sereda, P., Bartroli, A.V., Serlie, I.W., Gerritsen, F.A.: Visualization of boundaries in volumetric data sets using LH histograms. IEEE Trans. Vis. Comput. Graph. 12(2), 208–218 (2006)
Spitzer, V., Ackerman, M.J., Scherzinger, A.L., Whitlock, D.: The visible human male: a technical report. J. Am. Med. Inform. Assoc. 3(2), 118–130 (1996)
Zhang, B., Tao, Y., Lin, H., Dong, F., Clapworthy, G.: Intuitive transfer function design for photographic volumes. J. Vis. 18(4), 571–580 (2015)
Acknowledgments
This work was supported in part by National Natural Science Foundation of China No. 61472354 and the National Key Technology Research and Development Program of the Ministry of Science and Technology of China under Grant 2014BAK14B01.
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Zhang, B., Tao, Y., Lin, H. (2016). Robust Color Gradient Estimation for Photographic Volumes. In: El Rhalibi, A., Tian, F., Pan, Z., Liu, B. (eds) E-Learning and Games. Edutainment 2016. Lecture Notes in Computer Science(), vol 9654. Springer, Cham. https://doi.org/10.1007/978-3-319-40259-8_34
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DOI: https://doi.org/10.1007/978-3-319-40259-8_34
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