کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6856722 | 1437969 | 2018 | 23 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Pixel convolutional neural network for multi-focus image fusion
ترجمه فارسی عنوان
شبکه عصبی کانولوشه پیکسل برای تلفیق تصویر چند فوکوس
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کلمات کلیدی
فوکوس تصویر چند فوکوس شبکه عصبی متقاطع، یادگیری عمیق، تمرکز اندازه گیری،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
This paper proposes a pixel-wise convolutional neural network (p-CNN) that can recognize the focused and defocused pixels in source images from its neighbourhood information for multi-focus image fusion. The proposed p-CNN can be thought of as a learned focus measure (FM) and provides more efficiency than conventional handcrafted FMs. To enable the p-CNN with the strong capability to discriminate focused and defocused pixels, a comprehensive training image set based on a public image database is created. Furthermore, by setting precise labels according to different focus levels and adding various defocus masks, the p-CNN can accurately measure the focus level of each pixel in source images in which the artefacts in the fused image can be efficiently avoided. We also propose a method to implement the p-CNN with a conventional image convolutional neural network (image-wised CNN), which is almost 25 times faster than directly using the p-CNN in multi-focus image fusion. Experimental results demonstrate that the proposed method is competitive with or even outperforms the state-of-the-art methods in terms of both subjective visual perception and objective evaluation metrics.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volumes 433â434, April 2018, Pages 125-141
Journal: Information Sciences - Volumes 433â434, April 2018, Pages 125-141
نویسندگان
Tang Han, Xiao Bin, Li Weisheng, Wang Guoyin,