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A New Fast and Efficient Decision-Based Algorithm for Removal of High-Density Impulse Noises

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. 189-192 Authors: K. S. Srinivasan and D. Ebenezer Reporter: Ching-Chih Cheng. Outline. Introduction The Proposed Method

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A New Fast and Efficient Decision-Based Algorithm for Removal of High-Density Impulse Noises

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  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. 189-192 Authors: K. S. Srinivasan and D. EbenezerReporter: Ching-Chih Cheng

  2. Outline • Introduction • The Proposed Method • Experimental Results • Conclusions

  3. Introduction • Remove Impulse Noise and Restore Image Impulse Noise (Salt and Pepper Noise) Original Entity Corrupted Image Restored Image

  4. P(x,y) Pmax Pmin Unchanged 0 < 123 < 255 The Proposed Method (1/3) window of size 3*3

  5. Pmin Pmax Pmed Pmed Changed=Pmed 0 < 123 < 255 0 < 123 < 255 The Proposed Method (2/3) 123

  6. The Proposed Method (3/3) 123 Pmin Pmax Pmed 0 < 255 < 255 Changed=Pleft Not Satisfied

  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)

  8. Experimental Results (2/2) girl 70% noise girl 90% noise Lena 70% noise Lena 90% noise (a) (b) (c) (d) (e) (f) SMF Original Noisy 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.

  9. Conclusions • The proposed algorithm requires simple physical realization structures

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