Design of Linear Equalizers Optimized for the Structural Similarity Index

Abstract--We propose an algorithm for designing linear equalizers that maximize the structural similarity (SSIM) index between the reference and restored signals. The SSIM index has enjoyed considerable application in the evaluation of image processing algorithms. Algorithms, however, have not been designed yet to explicitly optimize for this measure. The design of such an algorithm is nontrivial due to the nonconvex nature of the distortion measure. In this paper, we reformulate the nonconvex problem as a quasi-convex optimization problem, which admits a tractable solution. We compute the optimal solution in near closed form, with complexity of the resulting algorithm comparable to complexity of the linear minimum mean squared error (MMSE) solution, independent of the number of filter taps. To demonstrate the usefulness of the proposed algorithm, it is applied to restore images that have been blurred and corrupted with additive white gaussian noise. As a special case, we consider blur...

• Type: Journal
• Year: 2008
• Where: TIP
• Authors: Sumohana S. Channappayya, Alan C. Bovik, Constantine Caramanis, Robert W. Heath Jr.
• Keywords: Algorithm, Image, Linear, TIP 2008