5 ms·
A simpler way of achieving the same thing is to duplicate the layer, blur the top layer heavily, and then set it to "divide".
by keenerd 9y ago
A simpler way of achieving the same thing is to duplicate the layer, blur the top layer heavily, and then set it to "divide".
- donquichotte 9y agoReally? Do you care to explain? What is the dividend and what is the divisor? Why can dividing a image by its low pass filtered version (or vice versa) be used to "clean up" the image, i.e. subtract the background, find main colors and cluster similar colors with k-means? What if the divisor has pixels near zero?
- deleted 9y ago[deleted]
- keenerd 9y agoAreas of low contrast become whiter and areas of high contrast become more saturated. It is also more robust than k-means. The author's algo will only work on scanned images. Photographed pages from a book will often have a slight shadow on half the page from the curvature. Blur-divide will clean this up. K-means will think you've used a lot of gray and not figure out that there are multiple background colors.
- 333c 9y agoI can confirm that the author's approach doesn't work well for photographed pages. I took a photograph[0] of a page of notes, and due to the shadow, the results[1] were very unsatisfactory. [0]: https://i.imgur.com/CLZHshT.jpg https://i.imgur.com/CLZHshT.jpg [1]: https://i.imgur.com/rrwca0m.jpg https://i.imgur.com/rrwca0m.jpg
- tkp 9y agointeresting trick, thanks for sharing ! [edit] Quick test here : https://imgur.com/a/6xOz1 https://imgur.com/a/6xOz1
- vidarh 9y agoI think that test illustrates it'll take quite a lot more to achieve what the tool in the article did...