FUSION OF MULTI FOCUS IMAGES USING GENETIC ALGORITHM


Article NameFUSION OF MULTI FOCUS IMAGES USING GENETIC ALGORITHM
AuthorsVeysel ASLANTAŞ , Ahmet Nusret TOPRAK , Rifat KURBAN , Emre BENDEŞ
Keywords TRGörüntü birleştirme , genetik algoritma , sınırlı alan derinliği.
KeywordsMulti-focus image fusion , genetic algorithm , depth of field.
Article Summary In applications of imaging systems, one major problem is limited depth of field which results in blurring parts of the captured image. However, in many areas such as microscopic imaging, industrial machine vision and surveillance applications, images that have large depth of field are preferred. In this paper, a novel multi-focus image fusion method is presented. The Multi-focus image fusion golden games of gold miner games is play online for depth of field by miner. The method, firstly, calculates optical transfer function of blurred parts located on source images by using a technique based on genetic algorithm. Then source images are artificially blurred by employing obtained transfer functions and sharp pixels of sources images are detected by using artificially blurred and source images. Eventually, sharp pixels of source images are transferred to build everywhere-in-focus fused image. Furthermore, proposed method and classical methods are compared in terms of quantitative and visual evaluation. According to the results of evaluations, proposed method outperforms classic methods.
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