Abstract
A hierarchical image fusion scheme is presented that preserves those details from the input images that are most relevant to visual perception. Results show that fused images present a more detailed representation of the scene and provide information that cannot be obtained by viewing the input images separately. Detection, recognition, and search tasks may therefore benefit from this fused image representation.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Burt PJ (1984) The pyramid as a structure for efficient computation. In: Rosenfeld A (ed) Multiresolution Image Processing and Analysis. Springer-Verlag, Berlin, pp 6–35
Burt PJ, Adelson EH (1983) The Laplacian pyramid as a compact image code. IEEE Transactions on Communications COM-31(4):532–540
Burt PJ, Adelson EH (1985) Merging images through pattern decomposition. In: Applications of Digital Image Processing VIII, Proceedings of SPIE 575, pp 173–181
Burton GJ, Haig ND, Moorhead IR (1986) A self-similar stack model for human and machine vision. Biological Cybernetics 53:397–403
Growley JL, Parker AC (1984) A representation for shape based on peaks and ridges in the difference of low-pass transform. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-6:156–170
Haralick RM, Lin C, Lee JSJ, Zhuang X (1987a) Multiresolution morphology. In: Proceedings of IEEE First International Conference on Computer Vision, IEEE Comp. Soc. Press, Washington, pp 516–520
Haralick RM, Sternberg SR, Zhuang X (1987b) Image analysis using mathematical morphology. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-9(4):532–550
Huang KS, Jenkins BK, Sawchuk AA (1989) Binary image algebra and optical cellular logic processor design. Computer Vision, Graphics and Image Processing 45:295–345
Koenderink JJ (1984) The structure of images. Biological Cybernetics 50:363–370
Koenderink JJ, Doorn AJ van (1978) Visual detection of spatial contrast; influence of location in the visual field, target extent and illuminance level. Biological Cybernetics 30:157–167
Koenderink JJ, Doorn AJ van (1982) Invariant features of contrast detection: An explanation in terms of selfsimilar detector arrays. Journal of Optical Society of America, 72:83–87
Maragos PA (1987) Tutorial on advances in morphological image processing and analysis. Optical engineering 26:623–632
O Ying-Lie, Toet A (1990) Mathematical morphology in hierarchical image representation. In: Proceedings of NATO ASI. The Formation, Handling and Evaluation of Medical Images. Springer-Verlag, New York. In press
Rosenfeld A (ed) (1984) Multiresolution Image Processing and Analysis. Springer-Verlag, New York
Serra J (1982) Image Analysis and Mathematical Morphology. Academic Press, New York
Serra J (ed) (1988) Alternating sequential filters. In: Image Analysis and Mathematical Morphology, Vol. 2: Theoretical Advances, pp 203–216. Academic Press, New York
Shih FY, Mitchell OR (1989) Threshold decomposition of gray-scale morphology into binary morphology. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-11(1):31–42
SPIDER Working Group (1983) SPIDER User's Manual. AIST MITI, Japan
Toet A (1989a) Image fusion by a ratio of low-pass pyramid. Pattern Recognition Letters 9:245–253
Toet A (1989b) A morphological pyramidal image decomposition. Pattern Recognition Letters 9:255–261
Toet A (1990) Morphological Multiresolution Image Representations. Report TNO-IZF Institute for Perception TNO
Toet A, Koenderink JJ, Zuidema P, Graaf CN de (1984) Image analysis-topological methods. In: DeConinck F (Ed) Information Processing in Medical Imaging. Martinus Nijhof, The Hague, pp 306–342
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Toet, A. Hierarchical image fusion. Machine Vis. Apps. 3, 1–11 (1990). https://doi.org/10.1007/BF01211447
Issue Date:
DOI: https://doi.org/10.1007/BF01211447