- I don't know what this means. Maybe you mean that the noise is so far away from the image data that you can threshold to find it, like "Salt and Pepper noise". If so, see my attached demos.
- You can scan the image and get a local window around the current pixel. Then apply whatever algorithm you want to that local window. Use nlfilter() for this. You don't have to create a binary image, though thresholding usually does. You can create whatever kind of image you want with your custom algorithm.
How can we can we perform accurate edge detection for grayscale images using adaptive edge detection schemes?
1 view (last 30 days)
Show older comments
Ashfaq Ahmed
on 30 Aug 2015
Commented: Ashfaq Ahmed
on 31 Aug 2015
In spite of using conventional edge thresholding schemes to check the performance on edges on images with lot of details.
- How it can perform thresholding to removes noise as well.
- How it can adaptively threshold for 0-255 at each pixel without converting into binary image?
0 Comments
Accepted Answer
Image Analyst
on 30 Aug 2015
I don't know what "conventional edge thresholding schemes" you used. I don't know what "performance on edges" means. I assume you did some kind of edge detection and you disagree with the edges that were found. Why?
To answer your specific questions:
More Answers (0)
See Also
Products
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!