Improved methods of estimating shape from shading using the light source coordinate system
Artificial Intelligence
SIGGRAPH '89 Proceedings of the 16th annual conference on Computer graphics and interactive techniques
Height and gradient from shading
International Journal of Computer Vision
Fractal modeling of natural terrain: analysis and surface reconstruction with range data
Graphical Models and Image Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fractal Geometry in Digital Imaging
Fractal Geometry in Digital Imaging
3-D Terrain from Synthetic Aperture Radar Images
CVBVS '00 Proceedings of the IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (CVBVS 2000)
A Radar Reflectance Model for Terrain Analysis Using Shape from Shading
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Terrain Modeling in Synthetic Aperture Radar Images Using Shape-from-Shading
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
A novel method for solving the shape from shading (SFS) problem
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
A new method for fractional Brownian motion interpolation
IEEE Transactions on Signal Processing
A Karhunen-Loeve-like expansion for 1/f processes via wavelets
IEEE Transactions on Information Theory
Wavelet analysis and synthesis of fractional Brownian motion
IEEE Transactions on Information Theory - Part 2
Fractal-Based Description of Natural Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parallel Hidden Hierarchical Fields for Multi-scale Reconstruction
EMMCVPR '09 Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Invariant image reconstruction from irregular samples and hexagonal grid splines
Image and Vision Computing
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We consider the problem of extracting surface shape from a single terrain image. Although fractal models play an important role in simulating terrain models, the various Shape-from-Shading (SFS) techniques that have been applied to this kind of problem have not been coupled with a fractal prior. In this paper, we define the SFS problem of terrain imaging as a fractal-regularized problem, and solve it using Maximum-A-Posterior (MAP) estimation. In addition, we also propose a relaxation algorithm based on Landweber iteration in order to solve it. The optimum terrain surface corresponding to the observed image does not have to be the convergent result. The result can be picked up during the process of iteration with the number of iterations specified by an image-based estimation method proposed in this paper. Experimental results on both simulated data and real data show that our algorithm can efficiently extract terrain surfaces, and is more accurate than some well-known SFS algorithms, including the Horn, Zheng-Chellappa, Tsai-Shah, Pentland linear, and Lee-Rosenfeld methods.