A comparative study of various pixel-based image fusion techniques as applied to an urban environment

Dahiya, Susheela; Garg, Pradeep; Jat, Mahesh Kumar

doi:10.1080/19479832.2013.778335

Cited by 44 publications

(18 citation statements)

References 4 publications

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“…Apart from confusion caused by optical signatures, urban development is spatially heterogeneous in different regions, and image quality may vary scene by scene [26]. On the other hand, better accuracy could be achieved if multi-sensor remote sensing data [27,28] and detailed census and socio-economic survey data can be taken into account. In addition, the satellite-derived Land Surface Temperature (LST) will enable a better understanding of the surface conditions across different urban landscapes [29].…”

Section: Land Cover Mapping Limitationmentioning

confidence: 99%

Delineating Urban Fringe Area by Land Cover Information Entropy—An Empirical Study of Guangzhou-Foshan Metropolitan Area, China

Huang

Zhou

2016

IJGI

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Abstract:Rapid urbanization has caused many environmental problems, such as the heat island effect, intensifying air pollution, pollution from runoff, loss of wildlife habitat, etc. Accurate evaluations of these problems demand an accurate delineation of the spatial extent of the urban fringe. Conceptual and analytical ambiguity of the urban fringe and a general lack of consensus among researchers have made its measurement very difficult. This study reports a compound and reliable method to delineate the urban fringe area using a case study. Based on the 'fringe effect' theory in landscape ecology, the existing land cover information entropy model for defining the urban fringe is renewed by incorporating scale theory, cartography and urban geography theory. Results show that the urban fringe area of Guangzhou and Foshan metropolitan area covers an area of 2031 km 2 , and it occupies over 31% of the total study area. Result evaluation by industry structure data shows satisfactory correspondence with different land cover types. This paper reports the method and outcome of an attempt to provide an objective, repeatable and generally applicable method for mapping its spatial extent from remote sensing imageries, and could be beneficial to relevant urban studies and urban fringe management projects.

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Section: Land Cover Mapping Limitationmentioning

confidence: 99%

Delineating Urban Fringe Area by Land Cover Information Entropy—An Empirical Study of Guangzhou-Foshan Metropolitan Area, China

Huang

Zhou

2016

IJGI

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“…Multi-source image fusion algorithms are implemented in two spaces: the space domain and the transform domain (Dahiya, Garg, and Jat 2013). Among these, the image fusion algorithm based on a multi-scale geometry analysis is widely used (Gamba 2014).…”

Section: Introductionmentioning

confidence: 99%

Multi-channel satellite cloud image fusion in the tetrolet transform domain

Zhang

Chen

Duanmu

et al. 2014

International Journal of Remote Sensing

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A novel multi-channel satellite cloud image fusion algorithm constructed in the tetrolet transform domain is proposed. Tetrolet is successfully applied in image denoising, image sparse representation, and image restoration. In this paper, tetrolet transform was introduced into the field of satellite cloud image fusion since its sparse degree is high. Tetrolet can describe the geometric structure feature of the satellite cloud image very well. First, tetrolet transform must be implemented into the multi-channel satellite cloud images to obtain low-and high-frequency coefficients and corresponding covering distribution values. Then, a Laplacian pyramid algorithm must be used to decompose the low-frequency portion in the tetrolet domain by averaging the values of its top layer and taking the maximum absolute values of the other layers. While reconstruction is implemented in this stage, the algorithm takes the maximum standard deviation of the high-frequency parts for each block in the tetrolet domain. Last, an inverse tetrolet transform must be used to obtain the final fused image. This paper compares the proposed image fusion algorithm to three similar image fusion algorithms: the curvelet image fusion algorithm, the non-subsampled contourlet transform (NSCT) image fusion algorithm, and the tetrolet image fusion algorithm. Mutual information, joint entropy, mean structural similarity (MSSIM), standard deviation, and average relative deviation are used as objective criteria to evaluate the quality of the fused images. In order to verify the efficiency of the proposed algorithm, the fusion cloud image is used to determine the centre location of eye and non-eye typhoons. Experimental results show that the proposed algorithm performs well when fusing the information in multi-channel satellite cloud images and improves the precision of locating the typhoon's centre. The proposed algorithm's comprehensive performance is superior to similar image fusion algorithms.

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“…The detailed process is demonstrated in the following: To avoid disturbing other factors, the experimental image used in this paper is ENVI example data with geometric registration and resampling. There was an article that discussed the effect influenced by the resampling methods and conclusion is that resampling methods do not have any significant effect on the final visual appearance of the fused images [33]. The determined factor of experiment performance is the algorithms themselves.…”

Section: The Image Fusion Frameworkmentioning

confidence: 99%

A Bidimensional Empirical Mode Decomposition Method for Fusion of Multispectral and Panchromatic Remote Sensing Images

Dong

Lin

et al. 2014

Remote Sensing

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This article focuses on the image fusion of high-resolution panchromatic and multispectral images. We propose a new image fusion method based on a Hue-Saturation-Value (HSV) color space model and bidimensional empirical mode decomposition (BEMD), by integrating high-frequency component of panchromatic image into multispectral image and optimizing the BEMD in decreasing sifting time, simplifying extrema point locating and more efficient interpolation. This new method has been tested with a panchromatic image (SPOT, 10-m resolution) and a multispectral image (TM, 28-m resolution). Visual and quantitative assessment methods are applied to evaluate the quality of the fused images. The experimental results show that the proposed method provided superior performance over conventional fusion algorithms in improving the quality of the fused images in terms of visual effectiveness, standard deviation, correlation coefficient, bias index and degree of distortion. Both five different land cover types WorldView-II images and three different sensor combinations (TM/SPOT, WorldView-II, 0.5 m/1 m resolution and IKONOS, 1 m/4 m resolution) validated the robustness of BEMD fusion performance. Both of these results prove the capability of the proposed BEMD method as a robust image fusion method to prevent color distortion and enhance image detail.

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A comparative study of various pixel-based image fusion techniques as applied to an urban environment

Cited by 44 publications

References 4 publications

Delineating Urban Fringe Area by Land Cover Information Entropy—An Empirical Study of Guangzhou-Foshan Metropolitan Area, China

Delineating Urban Fringe Area by Land Cover Information Entropy—An Empirical Study of Guangzhou-Foshan Metropolitan Area, China

Multi-channel satellite cloud image fusion in the tetrolet transform domain

A Bidimensional Empirical Mode Decomposition Method for Fusion of Multispectral and Panchromatic Remote Sensing Images

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