On properties of visual quality metrics in remote sensing applications

Oleg Ieremeiev; Vladimir Lukin; Krzysztof Okarma; Karen Egiazarian; Benoit Vozel

doi:10.2352/EI.2022.34.10.IPAS-354

On properties of visual quality metrics in remote sensing applications

Oleg Ieremeiev, Vladimir Lukin, Krzysztof Okarma, Karen Egiazarian, Benoit Vozel

Computing Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

5 Citations (Scopus)

Abstract

Visual quality is important for remote sensing data presented as grayscale, color or pseudo-color images. Although several visual quality metrics (VQMs) have been used to characterize such data, only a limited analysis of their applicability in remote sensing applications has been done so far. In this paper, we study correlation factors for a wide set of VQMs for color images with distortion types typical for remote sensing. It is demonstrated that there are many metrics that have very high Spearman rank order correlation, e.g. PSNR-based and SSIM-based metrics. Meanwhile, there are also metrics that are practically uncorrelated with others. A detailed analysis of VQMs that have the largest SROCC values and belong to different groups is presented in this paper.

Original language	English
Title of host publication	Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Processing: Algorithms and Systems, 2022
Volume	34
Edition	10
DOIs	https://doi.org/10.2352/EI.2022.34.10.IPAS-354
Publication status	Published - 2022
Publication type	A4 Article in conference proceedings
Event	IS and T International Symposium on Electronic Imaging: Image Processing: Algorithms and Systems - Duration: 17 Jan 2022 → 26 Jan 2022

Publication series

Name	IS and T International Symposium on Electronic Imaging Science and Technology
ISSN (Print)	2470-1173

Conference

Conference	IS and T International Symposium on Electronic Imaging: Image Processing: Algorithms and Systems
Period	17/01/22 → 26/01/22

Keywords

correlation analysis
neural network
remote sensing image
visual quality

Publication forum classification

Publication forum level 1

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
Computer Science Applications
Human-Computer Interaction
Software
Electrical and Electronic Engineering
Atomic and Molecular Physics, and Optics

Access to Document

10.2352/EI.2022.34.10.IPAS-354

Cite this

Ieremeiev, O., Lukin, V., Okarma, K., Egiazarian, K., & Vozel, B. (2022). On properties of visual quality metrics in remote sensing applications. In Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Processing: Algorithms and Systems, 2022 (10 ed., Vol. 34). (IS and T International Symposium on Electronic Imaging Science and Technology). https://doi.org/10.2352/EI.2022.34.10.IPAS-354

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title = "On properties of visual quality metrics in remote sensing applications",

abstract = "Visual quality is important for remote sensing data presented as grayscale, color or pseudo-color images. Although several visual quality metrics (VQMs) have been used to characterize such data, only a limited analysis of their applicability in remote sensing applications has been done so far. In this paper, we study correlation factors for a wide set of VQMs for color images with distortion types typical for remote sensing. It is demonstrated that there are many metrics that have very high Spearman rank order correlation, e.g. PSNR-based and SSIM-based metrics. Meanwhile, there are also metrics that are practically uncorrelated with others. A detailed analysis of VQMs that have the largest SROCC values and belong to different groups is presented in this paper.",

keywords = "correlation analysis, neural network, remote sensing image, visual quality",

author = "Oleg Ieremeiev and Vladimir Lukin and Krzysztof Okarma and Karen Egiazarian and Benoit Vozel",

note = "Publisher Copyright: {\textcopyright} 2022, Society for Imaging Science and Technology. jufoid=84313; IS and T International Symposium on Electronic Imaging: Image Processing: Algorithms and Systems ; Conference date: 17-01-2022 Through 26-01-2022",

year = "2022",

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language = "English",

volume = "34",

series = "IS and T International Symposium on Electronic Imaging Science and Technology",

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Ieremeiev, O, Lukin, V, Okarma, K, Egiazarian, K & Vozel, B 2022, On properties of visual quality metrics in remote sensing applications. in Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Processing: Algorithms and Systems, 2022. 10 edn, vol. 34, IS and T International Symposium on Electronic Imaging Science and Technology, IS and T International Symposium on Electronic Imaging: Image Processing: Algorithms and Systems, 17/01/22. https://doi.org/10.2352/EI.2022.34.10.IPAS-354

On properties of visual quality metrics in remote sensing applications. / Ieremeiev, Oleg; Lukin, Vladimir; Okarma, Krzysztof et al.
Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Processing: Algorithms and Systems, 2022. Vol. 34 10. ed. 2022. (IS and T International Symposium on Electronic Imaging Science and Technology).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

T1 - On properties of visual quality metrics in remote sensing applications

AU - Ieremeiev, Oleg

AU - Lukin, Vladimir

AU - Okarma, Krzysztof

AU - Egiazarian, Karen

AU - Vozel, Benoit

PY - 2022

Y1 - 2022

N2 - Visual quality is important for remote sensing data presented as grayscale, color or pseudo-color images. Although several visual quality metrics (VQMs) have been used to characterize such data, only a limited analysis of their applicability in remote sensing applications has been done so far. In this paper, we study correlation factors for a wide set of VQMs for color images with distortion types typical for remote sensing. It is demonstrated that there are many metrics that have very high Spearman rank order correlation, e.g. PSNR-based and SSIM-based metrics. Meanwhile, there are also metrics that are practically uncorrelated with others. A detailed analysis of VQMs that have the largest SROCC values and belong to different groups is presented in this paper.

AB - Visual quality is important for remote sensing data presented as grayscale, color or pseudo-color images. Although several visual quality metrics (VQMs) have been used to characterize such data, only a limited analysis of their applicability in remote sensing applications has been done so far. In this paper, we study correlation factors for a wide set of VQMs for color images with distortion types typical for remote sensing. It is demonstrated that there are many metrics that have very high Spearman rank order correlation, e.g. PSNR-based and SSIM-based metrics. Meanwhile, there are also metrics that are practically uncorrelated with others. A detailed analysis of VQMs that have the largest SROCC values and belong to different groups is presented in this paper.

KW - correlation analysis

KW - neural network

KW - remote sensing image

KW - visual quality

U2 - 10.2352/EI.2022.34.10.IPAS-354

DO - 10.2352/EI.2022.34.10.IPAS-354

M3 - Conference contribution

AN - SCOPUS:85132408368

VL - 34

T3 - IS and T International Symposium on Electronic Imaging Science and Technology

BT - Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Processing: Algorithms and Systems, 2022

T2 - IS and T International Symposium on Electronic Imaging: Image Processing: Algorithms and Systems

Y2 - 17 January 2022 through 26 January 2022

ER -

On properties of visual quality metrics in remote sensing applications

Abstract

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Conference

Keywords

Publication forum classification

ASJC Scopus subject areas

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