A comparative assessment of different methods for Landsat 7/ETM+  pansharpening

Rodríguez-Galiano, Víctor; Pardo‐Igúzquiza, Eulogio; Chica-Olmo, Mario; Mateos, Javier; Rigol-Sánchez, J.P.; Vega, Miguel

doi:10.1080/01431161.2012.691612

Cited by 13 publications

(6 citation statements)

References 37 publications

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“…The SSIM is a quantitative metric that gives relatively accurate similarity prediction [53], which correlates well with perceptual image fidelity [54]. This index is an improved version of the universal quality index [55]; proposed by Wang et al [56], and has gained widespread popularity because of its simple formulation and its applicability to different image processing tasks, e.g., image compression [57], pan-sharpening [58]- [60], image denoising [61], [62], image restoration [63], [64], or downscaling [60]. The SSIM index, considers three different components of similarity: Luminance comparison, contrast comparison, and structural similarity.…”

Section: Structural Similarity Indexmentioning

confidence: 99%

Synthetic Images for Evaluating Topographic Correction Algorithms

Sola

González-Audícana

Álvarez‐Mozos

et al. 2014

IEEE Trans. Geosci. Remote Sensing

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In the last years, many topographic correction (TOC) methods have been proposed to correct the illumination differences between the areas observed by optical remote sensors. Although the available number of TOC methods is high, the evaluation of their performance generally relies on the existence of precise land-cover information, and a standardized and objective evaluation procedure has not been proposed yet. In this paper, we propose an objective procedure to assess the accuracy of these TOC methods on the basis of simulated scenes, i.e., synthetically generated images. These images represent the radiance an optical sensor would receive under specific geometric and temporal acquisition conditions and assuming a certain land-cover type. A simplified method for creating synthetic images using the stateof-the-art irradiance models is proposed, both considering the real topography of a certain area [synthetic real (SR) image] or considering the relief of this area as being completely flat [synthetic horizontal image (SH)]. The comparison between the corrected image obtained by applying a TOC method to the SR and SH images of the same area, allows assessing the performance of each TOC algorithm. This comparison is quantitatively carried out using the structural similarity index. The proposed TOC evaluation procedure is applied to a specific case study in northern Spain to explain its implementation and demonstrate its potential. The procedure proposed in this paper could be also used to assess the behavior of TOC methods operating under different scenarios considering diverse topographic, geometrical, and temporal acquisition configurations.

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Section: Structural Similarity Indexmentioning

confidence: 99%

Synthetic Images for Evaluating Topographic Correction Algorithms

Sola

González-Audícana

Álvarez‐Mozos

et al. 2014

IEEE Trans. Geosci. Remote Sensing

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“…More than 1/3 of our study area was not affected by the data gaps and the glaciers' boundaries were manually delineated taking the interpolation uncertainties into account. The Landsat-11 multispectral bands (30 m) were pan-sharpened for visual improvement (Rodriguez-Galiano et al, 2012) panchromatic band (15 m) acquired by same satellite and on the same date.…”

Section: Gap Fill and Pan-sharpening Of Landsat Slc-off Datamentioning

confidence: 99%

Tracing glacier changes since the 1960s on the south slope of Mt. Everest (central Southern Himalaya) using optical satellite imagery

Thakuri¹,

Salerno²,

Smiraglia³

et al. 2013

Preprint

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Abstract. We contribute to the debate on glacial shrinkage in the Himalaya by analyzing glaciers in southern slopes of Mt. Everest that are characterized by extensive debris coverage and the highest elevation in the world. In this paper, we make a complete analysis from 1962 to 2011, considering five intermediate periods using optical satellite imagery. We found an overall surface area shrinkage of 13.0 ± 3%, an upward shift of 182 ± 9 m in snow-line altitude (SLA), a terminus retreat of 403 ± 9 m, and an increase of 17.6 ± 3% in debris coverage. The recession process of glaciers has been relentlessly continuous over the past fifty years. Furthermore, since early 1990s, we have observed an acceleration of the surface area shrinkage, which resulted in a median annual rate double that of the previous three decades (an increase from 0.27% a−1 to 0.46% a−1). Comparing the SLA over the same periods, it shifts upward with a velocity almost three times greater (from 2.2 ± 0.5 m a−1 to 6.1 ± 0.9 m a−1), which points to a worsening of the already negative mass balance of these glaciers. However, the increased recession velocity has only significantly affected glaciers with the largest sizes, which are located at higher altitudes and along the preferable south-oriented direction of the monsoons. Moreover, these glaciers present median upward shifts of the SLA that are double others; this finding leads to a hypothesis that Mt. Everest glaciers are shrinking, not only due to warming temperatures, but also as a result of weakening Asian monsoons registered over the last decades. We conclude that the shrinkage of these glaciers is less than that of others in the Himalayan range. Their position in higher elevations have surely reduced the impact of warming on these glaciers, but have not been excluded from a relentlessly continuous and slow recession process over the past fifty years.

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“…Experiments were conducted on a computer with HP 250G8 Core i7 1165G7‐8Gb‐512Gb SSD‐15.6″‐W10. All the simulations were conducted on Matlab 2018b 52 and some of the pansharpening methods supplied from References 2,53–55.…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, the detail‐carrying capacity of an image increases as its spectral and spatial resolution increases. Because images with high spectral and spatial resolution provide more information, they are more commonly used in remote sensing applications 1,2 . Optical‐based earth satellites extend their service‐life by separating the spatial data of the acquired image information into low‐ and high‐resolution parts.…”

Section: Introductionmentioning

confidence: 99%

“…Because images with high spectral and spatial resolution provide more information, they are more commonly used in remote sensing applications. 1,2 Optical-based earth satellites extend their service-life by separating the spatial data of the acquired image information into low-and high-resolution parts. High spectral resolution images are frequently used in remote sensing applications such as vegetation mapping, agriculture, navigation, disaster warning, change detection, spatial planning, and surveillance.…”

Section: Introductionmentioning

confidence: 99%

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Histogram modification based pansharpening by using differential evolution algorithm

PALANCIOĞLU

2022

Concurrency and Computation

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SUMMARY Optic geo‐observer satellites acquire multispectral images (MSI) with low spatial resolution and panchromatic images (PAN) with high spatial resolution, due to communication band‐limits and the necessity of using on‐board energy efficiently. Histogram modification is an image processing method that alters the intensity values of an image to improve contrast. The Histogram Modification based Pansharpening (HMP) method has been proposed in this article for injecting high‐resolution spatial information of PAN into MSI with limited color degeneration to generate a pansharpened image (PSI). The differential evolution algorithm (DE) has been used to optimize the internal parameters of the HMP. HMP uses three different blind‐image quality metrics to avoid from artificial spectral and spatial defects generally appeared in PSI. The quality of PSI generated by HMP has been statistically compared to the PSIs produced by 17 different pansharpening methods by using 10 different image quality metrics. In the tests performed, three different test image sets acquired by geo‐observation satellites have been used. Test image sets are covering the areas with different spatial and spectral characteristics. HMP outperforms the other state‐of‐the‐art pansharpening methods used in this article, according to the statistical analysis results. HMP is highly effective at reliably preserving spectral and spatial fidelity.

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A comparative assessment of different methods for Landsat 7/ETM+ pansharpening

Cited by 13 publications

References 37 publications

Synthetic Images for Evaluating Topographic Correction Algorithms

Synthetic Images for Evaluating Topographic Correction Algorithms

Tracing glacier changes since the 1960s on the south slope of Mt. Everest (central Southern Himalaya) using optical satellite imagery

Histogram modification based pansharpening by using differential evolution algorithm

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