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    The Effect of Dictionary Learning Algorithms on Super-resolution Hyperspectral Reconstruction
    (Ieee, 2015) Simsek, Murat; Polat, Ediz
    The spatial resolutions of hyperspectral images are generally lower due to imaging hardware limitations. Super-resolution algorithms can be applied to obtain higher resolutions. Many algorithms exist to achieve super-resolution hyperspectral images from low resolution images acquired in different wavelengths. One of the popular algorithms is sparse representation-based algorithms that employ dictionary learning methods. In this study, a comparative framework is developed to investigate which dictionary learning algorithm leads to better super-resolution images. In order to achieve that, K-SVD and ODL dictionary learning algorithms are employed for comparison. A sparse representation-based algorithm G-SOMP+ is used for hyperspectral super-resolution reconstruction. The experimental results show that ODL algorithm outperforms K-SVD in terms of both reconstruction quality and processing times.
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    Sparse Representation-based Dictionary Learning Methods for Hyperspectral Super-Resolution
    (Ieee, 2016) Simsek, Murat; Polat, Ediz
    Due to hardware limitations, hyperspectral imagery has low spatial resolution. It can be obtained super-resolution hyperspectral imagery by means of sparse representation-based methods that are designed for improving spatial resolution. In this paper, the effect of sparse representation-based dictionary learning algorithms including K-SVD, ODL and Bayes on obtaining superresolution images with low error and high quality has been investigated. The method with best results has been identified.
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    Wide Area Scanning Trap Camera System with Multi-Cameras and Distinctive Motion Detection Sensor
    (Ieee, 2018) Simsek, Murat; Yalcinkaya, Fikret; Ugurlutan, Rifat
    The Trap Camera Systems in lots of different fields such as defense, medical, ecological research, wildlife surveillance, reconnaissance and surveillance, scientific research, nest ecology, rare species detection, ecological population estimation and rich species identification, border security, illegal migration detection, habitat occupation, orienteering, sports activities, military and civilian target detection and sporting events, provide limited situational awareness with single camera and motion detection sensor having ability Access restricted distances. Unlike the conventional systems, in this paper, we present a wide-area scanning system, which is created with four cameras and image processing software, designed to penetrate far distances with a unique designed motion detection sensors. The designed system is adaptive and compact and extra features can be optionally added with completely original software.