A New Benchmark Based on Recent Advances in Multispectral Pansharpening: Revisiting Pansharpening With Classical and Emerging Pansharpening Methods

Vivone, Gemine; Mura, Mauro Dalla; Garzelli, Andrea; Restaino, Rocco; Scarpa, Giuseppe; Ulfarsson, Magnus O.; Alparone, Luciano; Chanussot, Jocelyn

doi:10.1109/mgrs.2020.3019315

Cited by 190 publications

(129 citation statements)

References 129 publications

Supporting

Mentioning

122

Contrasting

Order By: Relevance

“…II, Wald's protocol has been detailed pointing out the consistency and synthesis properties. The synthesis property is a condition both necessary and sufficient, under the hypothesis that the performance evaluated at reduced resolution is consistent with the assessment that would be performed at full resolution (the so-called "invariance among scale" [1], [2]). This is a crucial point requiring attention when simulated low spatial resolution products are generated starting from the original MS and PAN images.…”

Section: A Data Pre-processingmentioning

confidence: 99%

“…PANSHARPENING APPROACHES Several taxonomies have been considered in the pansharpening literature. Among them, the one based on four main classes has recently been widely used [2]. In particular, we have the component substitution and the multi-resolution analysis families that represent the classical approaches (deeply explored in [1]) and recent developments relying upon the variational optimization-based and machine learning classes.…”

Section: Dataset Descriptionmentioning

confidence: 99%

“…Pansharpening is a well know research topic in remote sensing and image processing [1], [2]. Pansharpening refers to a particular case of image reconstruction from multiresolution acquisitions in which a multispectral (MS) image is super-resolved with the aid of a panchromatic (PAN) (i.e., monochromatic) image of higher spatial resolution.…”

Section: Introductionmentioning

confidence: 99%

“…large number of pansharpening algorithms have appeared in the literature following different approaches such as based on heuristic schemes, variational optimization and machine learning [2].…”

Section: Introductionmentioning

confidence: 99%

“…An open source implementation of the main state-of-the-art pansharpening algorithms is publicly distributed in [4], which is related to the software toolbox described in [1]. An updated version 1 of the toolbox has been recently presented in [2], also including methods belonging to different pansharpening paradigms.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A Benchmarking Protocol for Pansharpening: Dataset, Preprocessing, and Quality Assessment

Vivone

Mura

Garzelli

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Self Cite

View full text Add to dashboard Cite

Comparative evaluation is a requirement for reproducible science and objective assessment of new algorithms. Reproducible research in the field of pansharpening of very high resolution images is a difficult task due to the lack of openly available reference datasets and protocols. The contribution of this work is three-fold and it defines a benchmarking framework to evaluate pansharpening algorithms. First, it establishes a reference dataset, named PAirMax, composed of 14 panchromatic and multispectral image pairs collected over heterogeneous landscapes by different satellites. Second, it standardizes various image pre-processing steps, such as filtering, upsampling, and band co-registration, by providing a reference implementation. Third, it details the quality assessment protocols for reproducible algorithm evaluation.

show abstract

Section: A Data Pre-processingmentioning

confidence: 99%

Section: Dataset Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Benchmarking Protocol for Pansharpening: Dataset, Preprocessing, and Quality Assessment

Vivone

Mura

Garzelli

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

The role of image interpolation in pansharpening

Yılmaz

2022

Concurrency and Computation

View full text Add to dashboard Cite

Pansharpening is an efficient way of producing images of higher spectral and spatial fidelity. Since pansharpening aims to generate a spectrally enhanced image with the same spatial detail content of the source panchromatic (PAN) image, the source multispectral (MS) image is upsampled to the size of the source PAN image prior to pansharpening. Several image interpolation algorithms have been proposed for this purpose, which may lead the analysts to a confusion as to which of these algorithms should be used for the best pansharpening performance. Hence, this study aimed to investigate the role of widely used image interpolation algorithms in the quality of the pansharpened images. For this purpose, the nearest neighbor interpolation, bilinear interpolation, bicubic interpolation, interpolation with a polynomial kernel of 23 coefficients (INTERP23) and cubic spline interpolation algorithms were tested through several pansharpening techniques on three test sites with different characteristics. Investigations revealed that upsampling the source MS images with the INTERP23 algorithm resulted in the pansharpened images with the optimum spectral and spatial quality.

show abstract

Log-Gabor directional region entropy adaptive guided filtering for multispectral pansharpening

Wang

Bai

et al. 2022

Appl Intell

View full text Add to dashboard Cite

A New Benchmark Based on Recent Advances in Multispectral Pansharpening: Revisiting Pansharpening With Classical and Emerging Pansharpening Methods

Cited by 190 publications

References 129 publications

A Benchmarking Protocol for Pansharpening: Dataset, Preprocessing, and Quality Assessment

A Benchmarking Protocol for Pansharpening: Dataset, Preprocessing, and Quality Assessment

The role of image interpolation in pansharpening

Log-Gabor directional region entropy adaptive guided filtering for multispectral pansharpening

Contact Info

Product

Resources

About