Abstract
We generate an image with many lighting equipments by fusing images with a few lighting equipments. In general, the principle of the superposition is discussed for the lighting. An image with two lighting equipments is generated by adding the pixel values of two images with a lighting equipment. But it is difficult to generate the image by adding the pixel values of two images as the internal parameter changes in the case of using a single-lens reflex camera with the sensitivity automatic control facilities. On the other hand, it is difficult to generate the image using traditional fusion methods. We introduce the image fusion space describing the relationship between traditional fusion methods. We propose the method selecting the fusion method for each pixel from the image fusion space. The fusion image is generated using the fusion methods with the parameter suited in the divided regions by searching image fusion space. We show the effectiveness by generating the fusion images with lighting equipments in the general environment.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Levin, A., Zomet, A., Weiss, Y.: Learning how to inpaint from global image statistics. In: Proc. of Ninth IEEE International Conference on Computer Vision, pp. 305–312 (2003)
Bertalmio, M., Sapiro, G., Caselles, V., Ballester, C.: Image inpainting. In: SIGGRAPH 2000, pp. 417–424 (2000)
Bertalmio, M., Bertozzi, A.L., Sapiro, G.: Navie-stokes fluid dynamics and image and video inpainting. In: Proc. IEEE Computer Vision and Pattern Recognition, vol. 1, pp. 355–362 (2001)
Toet, A.: Multiscale contrast enhancement with application to image fusion. Optical Engineering 31, 1026–1031 (1992)
De, I., Chanda, B.: A simple and efficient algorith for multifocus image fusion using morphological wavelets. Signal Processing, elsevia (2005)
Tapiador, F.J., Casanova, J.L.: An algorithm for the fusion of images based on jaynes maximum entropy method. Int. J. Remote Sensing 23, 777–785 (2002)
Li, H., Manjunath, B.S., Mitra, S.K.: Multisensor image fusion using the wavelet transform. Graphical Models Image Process. 57, 235–245 (1995)
Zhang, Z., Blum, R.S.: A categorization of multiscale decomposition-based image fusion schimes with a performance study for a digital camera application. Proc. IEEE 87, 1315–1326 (1999)
Rancin, T., Wald, L.: Fusion of high spatial and spectral resolution images: The arsis concept and its implementation. Photogrammetric Engineering and Remote Sensing 66, 19–61 (2000)
Pajares, G., del la Crus, J.M.: A wavelet-based image fusion tutorial. Pattern Recognition, 1855–1871 (2004)
Wang, A.H.: A new multiwavelet-based approach to image fusion. Journal of Mathematical Imaging and Vision 21, 177–192 (2004)
Pu, T.: Contrast-based image fusion using the discrite wavelet transform. Int. J. Remote Sensing 39, 2075–2082 (2000)
Shashua, A.: Geometry and photometry in 3d visual recognition. MIT, Cambridge (1992)
Behumeur, P.N., Kriegman, D.J.: What is the set of image of and object under all possible lighting conditions? In: Proc. IEEE Computer Vision and Pattern Recognition 1996, pp. 270–277 (1996)
Debevec, P., Hawkins, T., Tchou, C., Duiker, H., Sarokin, W., Sagar, M.: Acquiring the Reflectance Field of a Human Face. In: SIGGRAPH 2000, pp. 145–157 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Morita, S. (2010). Generating Shaded Image with Lighting Using Image Fusion Space. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6455. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17277-9_60
Download citation
DOI: https://doi.org/10.1007/978-3-642-17277-9_60
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17276-2
Online ISBN: 978-3-642-17277-9
eBook Packages: Computer ScienceComputer Science (R0)