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Linear Gaussian blur evolution for detection of blurry images
E. Tsomko, H. J. Kim, E. Izquierdo
Research output
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Contribution to journal
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Article
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peer-review
8
Citations (Scopus)
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Dive into the research topics of 'Linear Gaussian blur evolution for detection of blurry images'. Together they form a unique fingerprint.
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Keyphrases
Blurry Image
100%
Gaussian Blur
100%
Image Quality
66%
Image Area
66%
Local Image
33%
Detection Accuracy
33%
Exposure Time
33%
Scale Space
33%
Detection Efficiency
33%
Monte Carlo
33%
Blurriness
33%
Digital Camera
33%
Autofocus
33%
Motion Compensation
33%
Image Collection
33%
Storage Capacity
33%
Image Point
33%
Linear Scale-space
33%
Device Handling
33%
Compensation Function
33%
Automatic Detection
33%
Automatic Removal
33%
Space Curve
33%
Representative Image
33%
Evolution Curves
33%
Curve Evolution
33%
Engineering
Curve Evolution
100%
Scale Space
100%
Gaussian Blur
100%
Storage Capacity
50%
Blurriness
50%
Motion Compensation
50%
Exposure Time
50%
Local Image
50%
Space-Curves
50%
Linear Scale
50%
Digital Camera
50%