Hyperspectral Imagery Superresolution

Irmak, Hasan
Akar, Gözde
Yuksel, Seniha Esen
Despite their high spectral resolution, hyperspectral images have low spatial resolution which adversely affects the applications that use hyperspectral images. In this study, instead of the traditional way of using spectral images, abundances of the endmembers are used in resolution enhancement. In the proposed method, first, endmembers are extracted with the SISAL algorithm. Then, the abundance maps are estimated using FCLS. From the low resolution abundance maps, high resolution abundance maps are obtained with a total variation based minimization. Finally, high resolution hyperspectral images are constructed from high resolution abundance maps. The proposed method is tested on real hyperspectral images. The experimental results and comparative analysis show the effectiveness of the proposed method.


Hyperspectral Superpixel Extraction Using Boundary Updates Based on Optimal Spectral Similarity Metric
Çalışkan, Akın; Koz, Alper; Alatan, Abdullah Aydın (2015-07-31)
The high spectral resolution of hyperspectral images (HSI) requires a heavy processing load. Assigning each pixel to a group in the image, which is called superpixel, and processing the superpixels instead of the pixels is resorted as a means to overcome this challenge in the hyperspectral literature. In this paper, we propose an algorithm to segment a hyperspectral image into superpixels by means of iteratively updating the boundary pixels of superpixels. We first explore the optimal similarity metric for ...
Image fusion for improving spatial resolution of multispectral satellite images
Ünlüsoy, Deniz; Süzen, Mehmet Lütfi; Department of Geological Engineering (2013)
In this study, four different image fusion techniques have been applied to high spectral and low spatial resolution satellite images with high spatial and low spectral resolution images to obtain fused images with increased spatial resolution, while preserving spectral information as much as possible. These techniques are intensity-hue-saturation (IHS) transform, principle component analysis (PCA), Brovey transform (BT), and Wavelet transform (WT) image fusion. Images used in the study belong to Çankırı reg...
Irmak, Hasan; Akar, Gözde; Yuksel, Seniha Esen; Aytaylan, Hakan (2016-07-15)
Super-resolution Reconstruction (SRR) is technique to increase the spatial resolution of images. It is especially useful for hyperspectral images (HSI), which have good spectral resolution but low spatial resolution. In this study, we propose an improvement to our previous work and present a novel MAP-MRF (maximum a posteriori-Markov random Fields) based approach for the SRR of HSI. The key point of our approach is to find the abundance maps of an HSI and perform SRR on the abundance maps using MRF based en...
High dynamic range imaging pipeline on the GPU
Akyüz, Ahmet Oğuz (2015-06-01)
Use of high dynamic range (HDR) images and video in image processing and computer graphics applications is rapidly gaining popularity. However, creating and displaying high resolution HDR content on CPUs is a time consuming task. Although some previous work focused on real-time tone mapping, implementation of a full HDR imaging (HDRI) pipeline on the GPU has not been detailed. In this article we aim to fill this gap by providing a detailed description of how the HDRI pipeline, from HDR image assembly to ton...
An Investigation on hyperspectral image classifiers for remote sensing
Özdemir, Okan Bilge; Çetin, Yasemin; Department of Information Systems (2013)
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
H. Irmak, G. Akar, and S. E. Yuksel, “Hyperspectral Imagery Superresolution,” 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54710.