Abstract
Depth estimation is an important parameter for three-dimensional shape recovery. There are many factors affecting the depth estimation including luminance, texture reflectance, noise etc. In this paper, we limit our discussion to noise. We present noise analysis by first pre-filtering the noisy images using well known Wiener filter and then using a robust focus measure for depth estimation. That depth map can further be used in techniques and algorithms leading to recovery of three dimensional structure of the object. The focus measure is based on an optical transfer function implemented in the Fourier domain and its results are compared with the earlier focus measures and presented in this paper. The additive Gaussian noise is considered for noise analysis.
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Malik, A.S., Choi, TS. (2007). Noise Analysis for Depth Estimation. In: Mele, F., Ramella, G., Santillo, S., Ventriglia, F. (eds) Advances in Brain, Vision, and Artificial Intelligence. BVAI 2007. Lecture Notes in Computer Science, vol 4729. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75555-5_31
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DOI: https://doi.org/10.1007/978-3-540-75555-5_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75554-8
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