Denoising using projections onto the epigraph set of convex cost functions
2014 IEEE International Conference on Image Processing, ICIP 2014
Institute of Electrical and Electronics Engineers Inc.
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Please cite this item using this persistent URLhttp://hdl.handle.net/11693/28663
A new denoising algorithm based on orthogonal projections onto the epigraph set of a convex cost function is presented. In this algorithm, the dimension of the minimization problem is lifted by one and feasibility sets corresponding to the cost function using the epigraph concept are defined. As the utilized cost function is a convex function in RN, the corresponding epigraph set is also a convex set in RN+1. The denoising algorithm starts with an arbitrary initial estimate in RN+1. At each step of the iterative denoising, an orthogonal projection is performed onto one of the constraint sets associated with the cost function in a sequential manner. The method provides globally optimal solutions for total-variation, ℓ1, ℓ2, and entropic cost functions.1 © 2014 IEEE.
- Conference Paper 2294
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