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SSIM-optimal linear image restoration
S.S. Channappayya, A.C. Bovik, C. Caramanis and R.W. Heath Jr.
IEEE International Conference on
Acoustics, Speech, and Signal Processing
Abstract
In this paper, we present an algorithm for designing a linear equalizer
that is optimal with respect to the structural similarity (SSIM)
index. The optimization problem is shown to be non-convex, thereby
making it non-trivial. The non-convex problem is first converted to
a quasi-convex problem and then solved using a combination of first
order necessary conditions and bisection search. To demonstrate the
usefulness of this solution, it is applied to image denoising and image
restoration examples. We show using these examples that optimizing
equalizers for the SSIM index does indeed result in higher
perceptual image quality compared to equalizers optimized for the
ubiquitous mean squared error (MSE).
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