is there any filter other than gaussian filter to reduce noise? if so what filter can be used?
5 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
Shan Sha
el 18 de Sept. de 2018
Comentada: Shan Sha
el 18 de Sept. de 2018
I need other filter than gaussian filter to get better results. please suggest me
0 comentarios
Respuesta aceptada
Gurunath konka
el 18 de Sept. de 2018
Average and median filters are the other filters which reduces the noise in the images, but tends to blur the edges
0 comentarios
Más respuestas (1)
Image Analyst
el 18 de Sept. de 2018
What kind of data do you have? A 1-D signal? A 2-D grayscale or color image?
You can look at simple filters like median, average, Gaussian blur, or there are better but more complicated filters like BM3D, K-SVD, non-local means, Kuwahara (demo attached), K-LLD, etc. Last I checked BM3D was considered state of the art for images, and what everyone else tried to beat (usually unsuccessfully). There are non-local means submissions in the File Exchange.
You might look at this comprehensive overview by one of the leading image noise researchers: https://users.soe.ucsc.edu/~milanfar/publications/journal/ModernTour.pdf
3 comentarios
Image Analyst
el 18 de Sept. de 2018
I don't know what your algorithm is, but if you need a noise free image to start with, I'd suggest you start with synthetic, computer-generated images where you have a known, perfect, noise-free image, and then add noise of known characteristics to it. Or you can start with real world images and perhaps remove noise or not, and define those to be the perfect, noise-free images, but I'd recommend the synthetic image generation method first.
Ver también
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!