Fusion of LBP and Hu-Moments with Fisher Vectors in Remote Sensing Imagery

Tombe, Ronald; Viriri, Serestina

doi:10.1007/978-3-030-28377-3_33

Cited by 2 publications

(1 citation statement)

References 34 publications

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“…This field is well studied, as it is widely used in computer vision, image classification and segmentation. In remote sensing the image invariants are commonly used and the most prominent examples are algorithms for image registration [4,5], or scene classification [6,7]. In ocean remote sensing they are commonly implemented in algorithms for automatic oil spill detection [8,9].…”

Section: Introductionmentioning

confidence: 99%

Methodology based on the Hu moment invariants for object comparison on radar satellite imagery

Gancheva,

Peneva

2023

J. Phys.: Conf. Ser.

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In this paper we present a methodology for comparing objects, identified on satellite images acquired by Synthetic Aperture Radar (SAR). The methodology describes object transformations mathematically and provides a quantitative estimate of the similarity of different shapes. To demonstrate its capabilities we examine a case study – we detect an underwater structure in the Western Black Sea, which becomes visible on radar imagery under favourable sea conditions. Our aim is to quantitatively describe if it changes over time and to determine on which dates the detections reveal the greatest similarity. The suggested methodology is based on computation of the Hu moment invariants, or the image moments. They give a set of 7 invariants, which describe object transformations, such as translation, scale, rotation and reflection. The presented methodology can be applied in different contexts on satellite imagery for quantitative description of structure transformations.

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