Results 171 to 180 of about 1,639 (207)

Joint denoising and unmixing for hyperspectral image

2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2014
Hyperspectral image denoising and unmixing are two separate stages in traditional works. Unmixing algorithm is implemented after denoising. The performance of unmixing will be promoted if noise in hyperspectral image is removed well. But the result of unmixing can not be used to improve the result of denoising.
Yongqiang Zhao 0001, Jingxiang Yang, Chen Yi, Yong Liu   +3 more
openaire   +1 more source

The effect of denoising on superresolution of hyperspectral images

Image and Signal Processing for Remote Sensing XXIII, 2017
Hyperspectral Images (HSI) are usually affected by different type of noises such as Gaussian and non-Gaussian. The existing noise can directly affect the classification, unmixing and superresolution analyses. In this paper, the effect of denoising on superresolution of HSI is investigated. First a denoising method based on shearlet transform is applied
Eskandari, Armin, Karami, Azam
openaire   +2 more sources

Multiscale Windowed Denoising and Segmentation of Hyperspectral Images

2008 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, 2008
This paper presents the effects of multiscale windowed denoising of spectral signatures before segmentation of hyperspectral images. In the proposed denoising approach it is intended to exploit both spectral and spatial information of the hyperspectral images by using wavelets and principal component analysis.
Yildirim, Tülay, ERTÜRK, SARP, Bilgin, Gökhan   +2 more
openaire   +3 more sources

Hyperspectral image denoising using 3D wavelets

2012 IEEE International Geoscience and Remote Sensing Symposium, 2012
In this paper, we propose a denoising method for hyperspectral images using 3D wavelets. We use the sparse analysis regularization using a 3D overcomplete wavelet dictionary. The minimization problem is solved using iterative Chambolle algorithm. The simulation results show that the 3D dictionary outperforms the 2D one, in terms of Peak Signal to Noise
Behnood Rasti, Johannes R. Sveinsson, Magnus O. Ulfarsson, Jón Atli Benediktsson   +3 more
openaire   +1 more source

Fast Hyperspectral Image Denoising and Inpainting Based on Low-Rank and Sparse Representations

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018
This paper introduces two very fast and competitive hyperspectral image (HSI) restoration algorithms: fast hyperspectral denoising (FastHyDe), a denoising algorithm able to cope with Gaussian and Poissonian noise, and fast hyperspectral inpainting ...
Lina Zhuang, JOSÉ M Bioucas-Dias
exaly   +2 more sources

Mixed Gaussian and impulse denoising of hyperspectral images

2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015
Hyperspectral image denoising is an important preprocessing step in the analysis of hyperspectral images in several applicaitons domains. These images often gets corrupted by various kinds of noise during acquisition process. There are several studies on reducing Gaussian noise from hyperspectral images.
Hemant Kumar Aggarwal, Angshul Majumdar
openaire   +1 more source

Sparse unmixing based denoising for hyperspectral images

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016
Until recently, hyperspectral image denoising was considered as a prior step to applications such as classification, detection, or unmixing. However, unmixing has been recently shown to also provide denoising due to its inherent property of representing pixels in terms of pure material signatures and their abundances. It is possible to eliminate sensor-
openaire   +2 more sources

Unmixing-based denoising for destriping and inpainting of hyperspectral images

2014 IEEE Geoscience and Remote Sensing Symposium, 2014
Unmixing-based Denoising exploits spectral unmixing results to selectively recover bands affected by a low Signal-to-Noise Ratio in hypespectral images. This paper proposes to apply this algorithm, which operates pixelwise, for the inpainting of corrupted pixels and the removal of drop-out artifacts in hy-perspectral scenes.
Daniele Cerra, Rupert Müller, Peter Reinartz   +2 more
openaire   +1 more source

Hyperspectral Image Denoising with Realistic Data

2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021
Tao Zhang 0042, Ying Fu 0001, Cheng Li 0009   +2 more
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Hyperspectral light field image denoising

2017 International Conference on Optical Instruments and Technology: Optoelectronic Imaging/Spectroscopy and Signal Processing Technology, 2018
Hyperspectral light field (HSLF) images with enriched spectral and angular information provide better representation of real scenes than conventional 2D images. In this paper, we propose a novel denoising method for HSLF images. The proposed method consists of two main steps.
Zhen Cheng, Dong Liu, Na Qi, Yun Liu, Zhiwei Xiong   +4 more
openaire   +1 more source