A GENETIC ALGORITHM FOR LEARNING IMAGE BLUR AND SHARPEN FILTERS
Author(s) -
Sarab M. Hameed
Publication year - 2007
Publication title -
journal of al-nahrain university-science
Language(s) - English
Resource type - Journals
eISSN - 2519-0881
pISSN - 1814-5922
DOI - 10.22401/jnus.10.2.29
Subject(s) - sharpening , image (mathematics) , computer science , artificial intelligence , filter (signal processing) , algorithm , process (computing) , genetic algorithm , simple (philosophy) , computer vision , composite image filter , machine learning , philosophy , epistemology , operating system
This paper presents an approach for learning traditional image filters (blurring and sharpening). The concept of learning is based on the mechanism of Genetic algorithm (GA). By GA, filters applied on one source image can be learned and then used to process automatically another target image. By this way, blurring and sharpening can be implicitly deduced and applied without requiring to mathematically defining (i.e. explicitly) them. The proposed approach is simple and can provide good results; however, applying the filter directly is much more efficient.
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