Name
Title | ||
|---|---|---|
Simple adaptive median filter for the removal of impulse noise from highly corrupted images |
Abstract | ||
|---|---|---|
This paper presents a simple, yet efficient way to remove impulse noise from digital images. This novel method comprises two stages. The first stage is to detect the impulse noise in the image. In this stage, based on only the intensity values, the pixels are roughly divided into two classes, which are "noise-free pixel" and "noise pixel". Then, the second stage is to eliminate the impulse noise from the image. In this stage, only the "noise-pixels" are processed. The "noise-free pixels " are copied directly to the output image. The method adaptively changes the size of the median filter based on the number of the "noise-free pixels " in the neighborhood. For the filtering, only "noise-free pixels " are considered for the finding of the median value. The results from 100 test images showed that this proposed method surpasses some of the state-ofart methods, and can remove the noise from highly corrupted images, up to noise percentage of 95%. Average processing time needed to completely process images of 1600times1200 pixels with 95% noise percentage is less than 2.7 seconds. Because of its simplicity, this proposed method is suitable to be implemented in consumer electronics products such as digital television, or digital camera. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/TCE.2008.4711254 | IEEE Trans. Consumer Electronics |
Keywords | Field | DocType |
novel method,state-ofart method,noise-free pixel,impulse noise,method adaptively change,noise percentage,noise pixel,simple adaptive median filter,digital camera,corrupted image,digital television,digital tv,median filter,adaptive filters,switches,noise reduction,pixel,testing,digital images,digital filters,salt and pepper noise,filtering,adaptive filter,noise,digital image | Computer vision,Value noise,Median filter,Non-local means,Computer science,Dark-frame subtraction,Salt-and-pepper noise,Image noise,Electronic engineering,Artificial intelligence,Impulse noise,Gaussian noise | Journal |
Volume | Issue | ISSN |
54 | 4 | 0098-3063 |
Citations | PageRank | References |
34 | 1.61 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| H. Ibrahim | 1 | 249 | 11.16 |
| N. S.P. Kong | 2 | 189 | 7.76 |
| Theam Foo Ng | 3 | 41 | 4.86 |