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Need for artifact and textured region detection
Aim of the project Techniques used in the imaging world Approaches used Results Conclusion
Why do artifact detection ?
A lot of transformations lead to artifacts Few of them lead to loss in texture Main goal – repair/ replace the loss in texture
using texture from adjacent regions There are existing methods for replicating
texture Not many existing methods for detecting
regions where there is texture loss
Image: BarbaraLeft image compressed at 94%
The encircled areas show loss in texture due to compression
Aim of the project
Very subjective – depends a lot on prior experience and knowledge
Complete automated detection is very hard because of the subjective nature of the problem
Aim of this project: To locate regions near textured regions which may have been subject to texture loss
Techniques that work well
The topics covered under this project are very subjective – hence the title of this slide is ‘techniques that work well’ as against ‘state of the art approaches’
Detection of textured regions Gabor filters Difference of offset Gaussians
Segmentation Lots and lots of them
(e.g. thresholding, clustering methods such as k-means and fuzzy c-means, connected components, region growing, etc.)
Again, very subjective
Approaches taken
Analyze wavelet block decomposition for a change in the high frequency region Low resolution Higher miss probability
The image Barbara compressed at 94%
Solid black areas give regions with texture. Black lines are parts of
edges
Edge map of left image overlaid on the compressed image
Use of Gabor coefficients as they are fairly reliable in detecting textured regions (found at six different orientations and four different scales) Transformed image is adaptively thresholded
to minimize the inter-class variance (Ref: N. Otsu, "A Threshold Selection Method from Gray-Level Histograms," IEEE Transactions on Systems, Man, and Cybernetics, vol. 9, no. 1, pp. 62-66, 1979.)
Magnitude and phase information is used collectively to locate regions of high texture
Pictures speak a thousand words
White regions give borders and textured areas
An edge map of the left image overlaid on the compressed image
White regions give regions of high textures
An edge map of the left image overlaid on the compressed image