COMPARATIVE ANALYSIS OF SATELLITE IMAGES STITCHING METHODS BASED ON LOCAL FEATURE DETECTION.

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Bibliographic Details
Title:	COMPARATIVE ANALYSIS OF SATELLITE IMAGES STITCHING METHODS BASED ON LOCAL FEATURE DETECTION.
Alternate Title:	Порівняльний аналіз методів зшивання супутникових зображень на основі виявлення локальних ознак
Authors:	Riabko, A. V.¹ 2383870@stud.kai.edu.ua, Hrishnenko, V. Y.¹ 1744220@stud.kai.edu.ua
Source:	Electronics & Control Systems. 2025, Vol. 86 Issue 4, p86-92. 7p.
Subjects:	Remote sensing, Descriptor systems, Remote-sensing images, Feature extraction
Abstract:	This paper investigates feature-based methods for satellite image stitching under a unified evaluation framework. Four algorithms - SIFT, SURF, ORB and BRISK - are examined with respect to keypoint detection, descriptor formation, correspondence generation and geometric alignment. A standardized MATLAB workflow is employed: grayscale detection and description, nearest-neighbour matching with a ratio test, robust outlier rejection via RANSAC with model escalation and mask-based blending with content cropping. Approximately fifty image sets spanning diverse landforms are processed; a Sahara Desert example illustrates the protocol. The study's aim is to characterize the accuracy-efficiency trade-offs of vector (SIFT, SURF) and binary (ORB, BRISK) descriptors in realistic orbital conditions and to provide a transparent basis for method selection in remote-sensing workflows. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	This paper investigates feature-based methods for satellite image stitching under a unified evaluation framework. Four algorithms - SIFT, SURF, ORB and BRISK - are examined with respect to keypoint detection, descriptor formation, correspondence generation and geometric alignment. A standardized MATLAB workflow is employed: grayscale detection and description, nearest-neighbour matching with a ratio test, robust outlier rejection via RANSAC with model escalation and mask-based blending with content cropping. Approximately fifty image sets spanning diverse landforms are processed; a Sahara Desert example illustrates the protocol. The study's aim is to characterize the accuracy-efficiency trade-offs of vector (SIFT, SURF) and binary (ORB, BRISK) descriptors in realistic orbital conditions and to provide a transparent basis for method selection in remote-sensing workflows. [ABSTRACT FROM AUTHOR]
ISSN:	19905548
DOI:	10.18372/1990-5548.86.20627