Decision Based Detail Preserving Algorithm for the Removal
of Equal and Unequal Probability Salt and Pepper Noise in Images and Videos
Vasanth Kishorebabu1, Kumar
Karuppaiyan4, Nagarajan Govindan3, Ravi Natarajan2,
Sundarsingh Jebaseelan3, and Godwin Immanuel3
1Department of Electronics and
Communication Engineering, Vidya Jyothi Institute of
Technology, India
2Department of Electrical and Electronics
Engineering, Vidya Jyothi Institute of Technology, India
3Department of Electrical and Electronics
Engineering, Sathyabama University, India
4Department of Electronics and
Instrumentation Engineering, Sathyabama University, India
Abstract: A novel vicinity based algorithm for the elimination of equal and
unequal probability salt and pepper noise with a fixed 3x3 kernel is proposed.
The proposed method uses a tree based switching mechanism for the replacement
of corrupted pixel. The processed pixel is checked for 0 or 255; if found true
then the pixel is considered as noisy else termed non noisy and left unaltered.
If the pixel is noisy then it checks for the 4 neighbors of the processed
pixel. If all the 4 neighbors are noisy then mean of the 4 neighbors are
replaced. If any of the 4 neighbors are not noisy then the corrupted pixel is
replaced by unsymmetrical trimmed mean. Under high noisy conditions if all the
elements of the current processing window is noisy then global mean replaces
the corrupted pixel. The proposed algorithm exhibits better performance both
quantitatively and qualitatively over the standard and existing algorithms at
very high noise densities. The performance of the existing non linear filters
are outclassed by the proposed algorithm in terms of PSNR, IEF, MSE, and SSIM
and also preserves fine details of an image even at high noise densities. The
algorithm works well even for gray scale, color images and video.
Keywords: Unequal probability salt and pepper
noise, unsymmetrical trimmed mean, edge preservation.
Received July 6, 2014; accepted December 16, 2014