Denoising 3D models with attributes using soft thresholding

Michael Roy; Sebti Foufou; Frederic Truchetet

doi:10.1117/12.578791

1 November 2004 Denoising 3D models with attributes using soft thresholding

Michael Roy, Sebti Foufou, Frederic Truchetet

Proceedings Volume 5607, Wavelet Applications in Industrial Processing II; (2004) https://doi.org/10.1117/12.578791
Event: Optics East, 2004, Philadelphia, Pennsylvania, United States

Abstract

Recent advances in scanning and acquisition technologies allow the construction of complex models from real world scenes. However, the data of those models are generally corrupted by measurement errors. This paper describes an efficient single pass algorithm for denoising irregular meshes of scanned 3D model surfaces. In this algorithm, the frequency content of the model is assessed by a multiresolution analysis that requires only 1-ring neighbourhood without any particular parameterization of the model faces. Denoising is achieved by applying the soft thresholding method to the detail coefficients given by the multiresolution analysis. Our method is suitable for irregular meshes with appearance attributes such as normal vectors and colors. Some results of real world scene models denoised with the proposed algorithm are given to demonstrate its efficiency.

Citation Download Citation

Michael Roy, Sebti Foufou, and Frederic Truchetet "Denoising 3D models with attributes using soft thresholding", Proc. SPIE 5607, Wavelet Applications in Industrial Processing II, (1 November 2004); https://doi.org/10.1117/12.578791

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