Spatial Quality Assessment of Pan-Sharpened High Resolution Satellite Imagery Based on an Automatically Estimated Edge Based Metric

Javan, Farzaneh Dadrass; Samadzadegan, Farhad; Reinartz, Peter

doi:10.3390/rs5126539

Cited by 36 publications

(16 citation statements)

References 16 publications

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“…32 The quality assessment methods of image fusion can be divided into two classes: subjective assessments that involve visual comparison of colors and spatial details, and objective assessments that involve a set of predefined quality indicators. 32 The quality assessment methods of image fusion can be divided into two classes: subjective assessments that involve visual comparison of colors and spatial details, and objective assessments that involve a set of predefined quality indicators.…”

Section: Evaluation Indices Of Fusion Resultsmentioning

confidence: 99%

Enhanced hyperspherical color space fusion technique preserving spectral and spatial content

Sun

et al. 2015

J. Appl. Remote Sens

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The newly developed hyperspherical color space (HCS) fusion method is a cost-effective panchromatic (pan) sharpening technique, but it still suffers from local spectral distortion and insufficient overall spatial details. This paper attempts to improve the HCS fusion method by combining the spectrum gain modulation and wavelet transformation and presents a novel fusion method called enhanced HCS (EHCS) to mitigate the mentioned issue. This method mainly contains three steps. (1) The proposed method extracts the angular component from multispectral images through hyperspherical color transformation (HCT). (2) A modulated multispectral image is generated by using the spectrum gain modulation. Then, the spatial details of the modulated multispectral image are substituted with the spatial details of the pan image by multiscale wavelet decomposition. (3) Finally, the angular component and modulated detail image are integrated to achieve the fused image by the inverse HCT. To validate the proposed method, three high spatial resolution images, i.e., two WorldView-2 and one QuickBird datasets, acquired at Fujian, China, were used. The comparison with HCS method was also done. Both the visual and quantitative analysis demonstrate that the EHCS method can significantly preserve the spectral characteristics and enhance the spatial detail as well.

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Section: Evaluation Indices Of Fusion Resultsmentioning

confidence: 99%

Enhanced hyperspherical color space fusion technique preserving spectral and spatial content

Sun

et al. 2015

J. Appl. Remote Sens

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show abstract

“…In Khan's protocol [10] MTF based filters are used to extract high frequency information and the UIQI measure is used for comparison. In [18] MTFs are estimated automatically from the edge information in an image which makes this approach even more practical. Unfortunately, evidence or proof that such comparison of different spectral bands (narrow multispectral band and broad panchromatic band) is legitimate is missing.…”

Section: Quality Assessment Based On Panchromatic Image In High Resolmentioning

confidence: 99%

Joint Quality Measure for Evaluation of Pansharpening Accuracy

Palubinskas

2015

Remote Sensing

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Abstract:A new Joint Quality Measure (JQM), which is a sole measure, is proposed for quality ranking of pansharpening methods. It is based on a newly proposed Composite similarity measure, which consists of Means, Standard deviations and Correlation coefficient (CMSC), and is translation invariant with respect to means and standard deviations. The JQM itself consists of a weighted sum of two terms. The first term is measured between a low pass filtered pansharpened image and original multispectral image at a reduced/low resolution scale. The second term is measured between the intensity calculated from spectrally weighted pansharpened multispectral image and original panchromatic image in a high resolution scale. Experimental results show advantages of a new measure, JQM, for quality assessment of pansharpening methods on the one hand, and drawbacks or unexpected properties of the already known measure, Quality with No Reference (QNR), on the other hand.

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“…The image quality of the satellite images can be expressed by many technical parameters, such as the GSD, the modulation transfer function (MTF) and the signal-to-noise ratio (SNR) [3][4][5]. However, these parameters cannot completely describe the quality of the image [6], and they are used primarily in technical fields and by technical people, such as satellite designers, satellite manufacturers, optical engineers or electric engineers; as a result, the parameters provide quality information and feedback for these technical workers.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Image Interpretability of ZY-3 Sensor Corrected Panchromatic Nadir Data

Li¹,

Luo²,

Zhu³

2014

Remote Sensing

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Image quality is important for taking full advantage of satellite data. As a common indicator, the National Imagery Interpretability Scale (NIIRS) is widely used for image quality assessment and provides a comprehensive representation of image quality from the perspective of interpretability. The ZY-3 (Ziyuan-3) satellite is the first civil high resolution mapping satellite in China, which was established in 2012. So far, there has been no reports on adopting NIIRS as the common indicator for the quality assessment of that satellite image data. This lack of a common quality indicator results in a gap between satellite data users around the world and those in China regarding the understanding of the quality and usability of ZY-3 data. To overcome the gap, using the general image-quality equation (GIQE), this study evaluates the ZY-3 sensor-corrected (SC) panchromatic nadir (NAD) data in terms of the NIIRS. In order to solve the uncertainty resulting from the exceeding of the ground sample distance (GSD) of ZY-3 data (2.1 m) in GIQE (less than 2.03 m), eight images are used to establish the relationship between the manually obtained NIIRS and the GIQE predicted NIIRS. An adjusted GIQE is based on the relationship and verified by another five images. Our study demonstrates that the method of using adjusted GIQE for calculating NIIRS can be used for the quality assessment of ZY-3 satellite images and reveals that the NIIRS value of ZY-3 SC NAD data is about 2.79.

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Spatial Quality Assessment of Pan-Sharpened High Resolution Satellite Imagery Based on an Automatically Estimated Edge Based Metric

Cited by 36 publications

References 16 publications

Enhanced hyperspherical color space fusion technique preserving spectral and spatial content

Enhanced hyperspherical color space fusion technique preserving spectral and spatial content

Joint Quality Measure for Evaluation of Pansharpening Accuracy

Estimation of the Image Interpretability of ZY-3 Sensor Corrected Panchromatic Nadir Data

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