Name
Abstract | ||
|---|---|---|
Image corruption is a common phenomenon which occurs due to electromagnetic interference, and electric signal instabilities in a system. In this letter, a novel multi procedure Min-Max Average Pooling based Filter is proposed for removal of salt, and pepper noise that betide during transmission. The first procedure functions as a pre-processing step that activates for images with low noise corruption. In latter procedure, the noisy image is divided into two instances, and passed through multiple layers of max, and min pooling which allow restoration of intensity transitions in an image. The final procedure recombines the parallel processed images from the previous procedures, and performs average pooling to remove all residual noise. Experimental results were obtained using MATLAB software, and show that the proposed filter significantly improves edges over exiting literature. Moreover, Peak Signal to Noise Ratio was improved by 1.2 dB in de-noising of medical images corrupted by medium to high noise densities. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/LSP.2020.3016868 | IEEE SIGNAL PROCESSING LETTERS |
Keywords | DocType | Volume |
Noise measurement, Image restoration, Image edge detection, Benchmark testing, Correlation, PSNR, Noise reduction, Mean filters, median filters, salt and pepper noise, pooling, image restoration and de-noising | Journal | 27 |
ISSN | Citations | PageRank |
1070-9908 | 3 | 0.39 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Piyush Satti | 1 | 3 | 0.39 |
| Nikhil Sharma | 2 | 3 | 0.39 |
| Bharat Garg | 3 | 32 | 9.88 |