1. A New Fast and Efficient Decision-Based Algorithm for Removal of High-Density Impulse Noises
Source: IEEE Signal Processing Letters, Vol. 14, No. 3, Mar. 2007, pp
Authors: K. S. Srinivasan and D. Ebenezer Reporter: Ching-Chih Cheng
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2. Outline Introduction The Proposed Method Experimental Results
Conclusions
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3. (Salt and Pepper Noise)
Introduction
Remove Impulse Noise and Restore Image
Impulse Noise
(Salt and Pepper Noise)
Original Entity
Corrupted Image
Restored Image
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4. The Proposed Method (1/3)
window of size 3*3
0 < 123 < 255
P(x,y)
Pmin
Pmax
Unchanged
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5. The Proposed Method (2/3)
0 < 123 < 255
Pmed
Pmin
Pmax
Changed=Pmed
123
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6. The Proposed Method (3/3)
123
Pmin
Pmed
Pmax
0 < 255 < 255
Changed=Pleft
Not Satisfied
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7. Experimental Results (1/2)
PSNR and Computation Time for Various Filters for Lena Image at Difference Noise Densities
SMF (standard median filter )
AMF (adaptive median filter )
TDF (threshold decomposition filter )
PA (proposed algorithm)
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8. Experimental Results (2/2)
girl
70% noise
girl
90% noise
Lena
70% noise
Lena 90% noise
(a) (b) (c) (d) (e) (f)
Original
Noisy
SMF
AMF
TDF PA
(a) Original image. (b) Noisy corrupted image. (c) Output for SMF. (d) Output for AMF. (e) Output for TDF. (f) Output for PA. Row 1 shows the girl image corrupted by 70% noise. Row 2 shows the girl image corrupted by 90% noise.
Row 3 shows the Lena image corrupted by 70% noise. Row 4 shows the Lena image corrupted by 90% noise.
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9. Conclusions
The proposed algorithm requires simple physical realization structures
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