Ataman, Ferhat Can
Akar, Gözde
© 2021 IEEE.The aim of multispectral image fusion is to combine object or scene features of images with different spectral characteristics to increase the perceptual quality. In this paper, we present a novel learning-based solution to image fusion problem focusing on infrared and visible spectrum images. The proposed solution utilizes only convolution and pooling layers together with a loss function using no-reference quality metrics. The analysis is performed qualitatively and quantitatively on various datasets. The results show better performance than state-of-the-art methods. Also, the size of our network enables real-time performance on embedded devices. Project codes can be found at pyFusionSR.
2021 IEEE International Conference on Image Processing, ICIP 2021


Visible And Infrared Image Fusion Using Encoder-Decoder Neural Network
Ataman, Ferhat Can; Akar, Gözde; Department of Electrical and Electronics Engineering (2021-9-07)
The image fusion aims to gather all important information from the source images into a single image. While the data is reduced, the fusion image has a high spa- tial and spectral resolution. It includes more informative and complete information. In this work, we reviewed state-of-the-art methods in the infrared and visible spec- trum image fusion literature and we present a novel deep learning-based solution. Our proposed method is inspired by encoder-decoder network U-Net architecture [1]. Furthermore...
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Hyperspectral image processing is improved by the capabilities of multispectral image processing with high spectral resolution. In this thesis, we explored hyperspectral classification with Support Vector Machines (SVM), Maximum Likelihood (ML) and KNearest Neighborhood algorithms. We analyzed the effect of training data on classification accuracy. For this purpose, we implemented three different training data selection methods; first N sample selection, randomly N sample selection and uniformly N sample se...
Citation Formats
F. C. Ataman and G. Akar, “VISIBLE AND INFRARED IMAGE FUSION USING ENCODER-DECODER NETWORK,” Alaska, Amerika Birleşik Devletleri, 2021, vol. 2021-September, Accessed: 00, 2022. [Online]. Available: