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Pattern Analysis and Applications
Erschienen in: Pattern Analysis and Applications 2/2024

01.06.2024 | Theoretical Advances

A novel Venus’ visible image processing neoteric workflow for improved planetary surface feature analysis

verfasst von: Indranil Misra, Mukesh Kumar Rohil, SManthira Moorthi, Debajyoti Dhar

Erschienen in: Pattern Analysis and Applications | Ausgabe 2/2024

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Abstract

The article presents a novel methodology that comprises of end-to-end Venus’ visible image processing neoteric workflow. The visible raw image is denoised using Tri-State median filter with background dark subtraction, and then enhanced using Contrast Limited Adaptive Histogram Equalization. The multi-modal image registration technique is developed using Segmented Affine Scale Invariant Feature Transform and Motion Smoothness Constraint outlier removal for co-registration of Venus’ visible and radar image. A novel image fusion algorithm using guided filter is developed to merge multi-modal Visible-Radar Venus’ image pair for generating the fused image. The Venus’ visible image quality assessment is performed at each processing step, and results are quantified and visualized. In addition, fuzzy color-coded segmentation map is generated for crucial information retrieval about Venus’ surface feature characteristics. It is found that Venus’ fused image clearly demarked planetary morphological features and validated with publicly available Venus’ radar nomenclature map.

Graphical abstract

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Metadaten
Titel
A novel Venus’ visible image processing neoteric workflow for improved planetary surface feature analysis
verfasst von
Indranil Misra
Mukesh Kumar Rohil
SManthira Moorthi
Debajyoti Dhar
Publikationsdatum
01.06.2024
Verlag
Springer London
Erschienen in
Pattern Analysis and Applications / Ausgabe 2/2024
Print ISSN: 1433-7541
Elektronische ISSN: 1433-755X
DOI
https://doi.org/10.1007/s10044-024-01253-4

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