Performance Analysis of Contourlet-Based Hyperspectral Image Fusion Methods

Choi, Yoonsuk; Sharifahmadian, Ershad; Latifi, Shahram

doi:10.5121/ijit.2014.2401

Cited by 10 publications

(9 citation statements)

References 34 publications

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“…For reconstruction, inverse Contourlet transform has to be applied. The basic flow of Contourlet based fusion framework (Choi et al 2013) is shown in Fig. 2.…”

Section: Contourlet Based Fusion (Ct)mentioning

confidence: 99%

Comprehensive review on fusion techniques for spatial information enhancement in hyperspectral imagery

Mookambiga

Gomathi²

2016

Multidim Syst Sign Process

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The volume of data grows with the advent of multiple types of remote sensing sensors and in order to extract the most useful information there is a need to combine the data gathered from the different sources. The widely used panchromatic and multispectral imageries in many applications offer decimetric and metric spatial resolution. However, the spectral resolution of these images is poor. Hyperspectral imaging has unique characteristics of providing very fine spectral resolution in a large number of bands with decametric spatial resolution and found to be highly useful for a wide span of application areas that requires high spectral resolution. The fusion of spectral and spatial information provides an effective way of enhancing the spatial quality of hyperspectral imagery as well as a method for preserving spectral quality. This fusion process is not a trivial task as always there has been a tradeoff between the preservation of spatial and spectral quality information as in the original sources of fusion. In this paper, a review on hyperspectral pansharpening and hyperspectral multispectral fusion based approaches has been reported. The widely adopted quantitative and qualitative performance measures to verify the fusion results are highlighted. In addition, the challenges in existing fusion techniques have also been discussed.

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“…For reconstruction, inverse Contourlet transform has to be applied. The basic flow of Contourlet based fusion framework (Choi et al 2013) is shown in Fig. 2.…”

Section: Contourlet Based Fusion (Ct)mentioning

confidence: 99%

Comprehensive review on fusion techniques for spatial information enhancement in hyperspectral imagery

Mookambiga

Gomathi²

2016

Multidim Syst Sign Process

View full text Add to dashboard Cite

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“…Furthermore, wideband detection can perform in dust-filled environments, where infrared and optical systems fail [17]- [19]. Hyperspectral sensors and infrared system provides good resolution through exterior layers of an object [20]- [23]. However, penetration through denser objects (e.g.…”

Section: Wideband Technologymentioning

confidence: 98%

Modeling techniques for target detection

2014

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To better study hyperspectral imaging sensors and remote sensing system performance, different parts of the remote sensing system can be modeled.Here, a scientific overview of recent modeling techniques is presented to come up with an appropriate approach for modeling of a target detection system. In particular, this study focuses on the development in modeling of scene, sensors, and processing algorithms. Moreover, the parallelization of the detection methods is emphasized for which the process of target detection accelerates. In conclusion, an appropriate model to evaluate a target detection system can be a hybrid model in which hyperspectral sensors, radars, and local sensors have been modeled.

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“…These methods are theoretically clear, but their framework is complex for estimation and the occurrence of incomplete deconvolution may result in an inefficient model. Multiscale and multiresolution methods extract high-frequency parts from HGRI and inject them into HSRI by decomposing the source image in a specific domain [17] [18] [19] [20] [21]. However, this type of method is highly dependent on the spectral properties of sampling methods and fails to intensify the spatial resolution of all bands.…”

Section: State Of the Artmentioning

confidence: 99%

“…Formulas (17) and 18have a similar mathematical form. Therefore, the ultimate fusion model can be achieved by replacing the variables in Formula (18) and updating rules in Formula (19) with the corresponding counterparts in Formula (17).…”

Section: Fusion Implementationmentioning

confidence: 99%

Image Fusion in Remote Sensing Based on Spectral Unmixing and Improved Non - negative Matrix Factorization Algorithm

He¹,

Wang²,

Lai³

et al. 2018

JESTR

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The spectral resolution of images improves with the continuous development of imaging technology in remote sensing. Traditional image fusion technologies result in problems in hyperspectral image fusion, such as spectral distortion and unclear physical meaning. A fast model based on improved non-negative matrix factorization (INMF) for hyperspectral and panchromatic image fusion was proposed to optimize the results of image fusion. First, the hyperspectral image was decomposed into endmember and abundance matrices using the INMF algorithm. The panchromatic image was then used to sharpen the abundance matrix. The spectral and sparse constraints were imposed on the objective function of the model. Finally, the resultant fused image was obtained by reconstructing the resolved endmember and abundance matrices. Results show that the proposed method is superior to other methods in terms of subjective assessment and objective analysis. As far as the indices of information entropy, correlation coefficient, Q-average, and spectral divergence are concerned, the proposed method surpasses those of second-best methods (Ehler, classical NMF, Ehler and Ehler) by 2.06%, 0.36%, 0.91%, and 56.31%, respectively, in the synthetic data experiment, and exceeds those of the second-best methods (Ehler, high-pass filtering, high-pass filtering and Ehler) by 0.13%, 10.05%, 3.89%, and 7.26%, respectively, in the real data experiment. Moreover, runtime is proportional to data size, and the proposed method takes the least time when image size is between 1 MB and 480 MB. This study provides theoretical reference for fast hyperspectral and panchromatic image fusion.

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Performance Analysis of Contourlet-Based Hyperspectral Image Fusion Methods

Abstract: ABSTRACT

Cited by 10 publications

References 34 publications

Comprehensive review on fusion techniques for spatial information enhancement in hyperspectral imagery

Comprehensive review on fusion techniques for spatial information enhancement in hyperspectral imagery

Modeling techniques for target detection

Image Fusion in Remote Sensing Based on Spectral Unmixing and Improved Non - negative Matrix Factorization Algorithm

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