An expeditious cum efficient algorithm for salt-and-pepper noise removal and edge-detail preservation using cardinal spline interpolation

• Salt-and-pepper impulse noise removal for noise densities up to 95%.
• Edge-Detail preservation with PSNR for noise densities up to 95%.
• The variation of the parameters α and β to maximize the PSNR.
• The comparative analysis and time complexity with existing algorithms.

This work proposes a faster and an efficient way to remove salt-and-pepper impulse noise and edge-preserving regularization of the henceforth obtained image. In this paper, we propose a two phase mechanism where the noisy pixels are identified and removed in the first phase. The detected noisy pixels in the first phase are involved in cardinal spline edge regularization process in the second phase. Promising results were found even for Noise levels as high as 95% with the proposed algorithm. The results were found to be much better than the previously proposed nonlinear filters or regularization methods both in terms of noise removal as well as edge regularization.

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