Region based multi-spectral fusion method for remote sensing images using differential search algorithm and IHS transform

Kurban, Tuba

doi:10.1016/j.eswa.2021.116135

Cited by 19 publications

(5 citation statements)

References 40 publications

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“…Hue is the dominant wavelength of the color inputs and defines the circumferential angle of the cylinder. Saturation is the purity of a color or the amount of white light in the image and defines the radius of the cylinder [21,22]. In the HIS each pixel is represented by a three-dimensional coordinate position within a color cube.…”

Section: Georeferencing and Enhancement Of The Imagesmentioning

confidence: 99%

Urban land use change study in Ulaanbaatar city using RS and GIS

Damdinsuren,

Amarsaikhan,

Gurjav

et al. 2023

J. Inst. Math. Digit. Technol.

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In recent years, Ulaanbaatar, the capital of Mongolia, has experienced very rapid urbanization. Different reasons are considered for urban expansion, however, the main cause is connected with a mass movement of rural people seeking for improved living conditions. The aim of this study is to analyse changes in urban land use in the central part of the capital city using remote sensing (RS) and geographic information system (GIS) datasets. For the development of the principal digital spatial database, a 1:5000 scale topographic map and a historical description of the elements of land use were used. To update the database and extract reliable urban land use information, very high-resolution panchromatic and multispectral Quickbird images of 2023 were fused. For fusion, three different data fusion techniques such as a Brovey transform, Gramme-Schmidt method and intensity-hue-saturation (IHS) transformation were compared in terms of the enhancement of spatial and spectral variations of the available classes. Of these methods, the IHS transformation gave a superior result in terms of both spectral and spatial separations between different objects and classes. Therefore, for this technique was selected for further analysis. Overall, the research showed that the central part of Ulaanbaatar city became very dense and precise planning should be considered. Улаанбаатарын хотын газар ашиглалтын өөрчлөлтийг зайнаас тандах судлал ба ГМС ашиглан судалсан дүн Сүүлийн жилүүдэд Монгол улсын нийслэл Улаанбаатарт хотжилт маш хурдацтай нэмэгдэж байна. Хотжилт тэлэх олон шалтгаан бий боловч гол шалтгаан нь амьдралын нөхцөлийг сайжруулахыг эрэлхийлж буй хөдөөгийн иргэдийн шилжилт хөдөлгөөнтэй холбоотой юм. Энэхүү судалгааны зорилго нь зайнаас тандах судлал (ЗТС) болон газарзүйн мэдээллийн систем (ГМС)-ийн өгөгдлийг ашиглан нийслэлийн төв хэсгийн газар ашиглалтын өөрчлөлтөд дүн шинжилгээ хийх юм. 1:5000 масштабтай байр зүйн зураг болон газар ашиглалтын элементүүдийн түүхэн өгөгдлүүдээр орон зайн мэдээллийн санг бүрдүүлэн судалгаанд ашигласан болно. Мэдээллийн санг шинэчилж хотын газрын ашиглалтын бодит мэдээллийг гарган авахын тулд Quickbird дагуулын 2023 оны хэт өндөр нарийвчлалтай панхроматик болон олон бүсчлэлийн зургуудыг нэгтгэн ашиглалаа. Дүрс мэдээг нэгтгэхдээ ангиудын орон зайн болон спектрийн тодролыг сайжруулах үүднээс Бровейн шилжүүлэлт, Грамм-Шмидтийн арга ба өнгө-эрчим-ханалт (IHS) хувиргалтын аргуудыг ашиглан үр дүнгүүдийг харьцуулсан. Эдгээр аргуудаас IHS-ийн хувиргалтын үр дүн нь өөр өөр объект болох ангиуд хоорондын спектрийн болон орон зайн хувьд хамгийн сайн ялгаж байсан тул цаашдын дүн шинжилгээнд сонгосон. Энэхүү судалгааны үр дүн нь Улаанбаатар хотын төв хэсэг хэт их нягтшилтай, нарийн төлөвлөлт хийх шаардлагатай байгааг харууллаа. Түлхүүр үгс: Хотын газар ашиглалт, Зайнаас тандан судлал, дүрс мэдээг нэгтгэх, өөрчлөлтийн судалга

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Section: Georeferencing and Enhancement Of The Imagesmentioning

confidence: 99%

Urban land use change study in Ulaanbaatar city using RS and GIS

Damdinsuren,

Amarsaikhan,

Gurjav

et al. 2023

J. Inst. Math. Digit. Technol.

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“…When it comes to spatial resolution, the MSI which has color information is less precise than the PAN image. Fused high-resolution images with complementary data from multispectral bands are necessary for remote sensing applications such as feature extraction, classification, change detection, and clustering (Kurban, 2022). Pan sharpening is the term specifically used to describe image fusion techniques used to Tuba ÇAĞLIKANTAR, Melih Can KILIÇ GU J Sci, Part A 11(1) 24-40 (2024) 10.54287/gujsa.1407864 produce an image with both color information and high spatial resolution.…”

Section: Introductionmentioning

confidence: 99%

A New and Efficient Pan Sharpening Method Based on Optimized Pixel Coefficients

Çağlıkantar,

Kılıç

2024

Gazi University Journal of Science Part A: Engineering and Innovation

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Pan sharpening aims to create a multispectral, high spatial resolution image by combining the multispectral image (MSI) with a high spatial resolution panchromatic image (PAN). Pan sharpening methods are performed between the MS image, which is the MSI image brought to PAN dimensions with the help of interpolation, and the PAN image. In this study, PAN sharpening is approached as an optimization problem. It is assumed that the optimal solution consists of multiplying the pixels of the MS image by optimized coefficients. It would be costly to optimize all the coefficients in this coefficient matrix one by one. For this reason, these coefficients were tried to be found with 5 different optimization-based methods. It was also compared with 19 different methods commonly used in the literature. 6 different evaluation criteria were used for this comparison. These comparisons were made on 3 different datasets. It has been observed that the proposed methods are superior to other methods.

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“…This issue causes the loss of intricate details in the fused image due to straightforward pixel-wise substitution. To address this shortcoming, a combined methodology intertwining the differential search algorithm, adaptive regional segmentation, IHS conversion, and RGB band processing was proposed [20]. Principal Component Analysis (PCA) is an image fusion technique that amalgamates multiple images by reducing data dimensions and extracting essential features [21].…”

Section: Introductionmentioning

confidence: 99%

An Optimized Inversion Method for Hyperspectral Image Fusion Based on a Hue–Intensity–Saturation, Wavelet, and Trust-Region Conjugate Gradient Method

Wu,

Ge,

Liu

et al. 2024

Electronics

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In hyperspectral remote sensing, achieving high spatial resolution holds paramount importance for an array of applications, such as environmental monitoring, geographic mapping, and precision agriculture. Nevertheless, conventional hyperspectral images frequently grapple with the issue of restricted spatial resolution. We apply optimized inversion methods to hyperspectral image fusion and present an innovative approach for hyperspectral image fusion which combines the Hue–Intensity–Saturation (HIS) transform, the wavelet transform, and the Trust-Region Conjugate Gradient technique. This amalgamation not only refines spatial precision but also augments spectral faithfulness, which is a pivotal aspect for applications like precise object detection and classification. In the context of our investigation, we conducted a thorough validation of our proposed HIS, Wavelet, and Trust-Region Conjugate Gradient (TRCG-HW) method for image fusion using a comprehensive suite of evaluation metrics. These metrics encompassed the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Correlation Coefficient (CC), Spectral Angle Mapper (SAM), and Error Relative Global Accuracy Score (ERGAS). The findings incontrovertibly establish TRCG-HW as the preeminent method among those considered. Our study effectively tackles the pressing predicament of low spatial resolution encountered in hyperspectral imaging. This innovative paradigm harbors the potential to revolutionize high-resolution hyperspectral data acquisition, propelling the field of hyperspectral remote sensing forward and efficiently catering to crucial application.

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Region based multi-spectral fusion method for remote sensing images using differential search algorithm and IHS transform

Cited by 19 publications

References 40 publications

Urban land use change study in Ulaanbaatar city using RS and GIS

Urban land use change study in Ulaanbaatar city using RS and GIS

A New and Efficient Pan Sharpening Method Based on Optimized Pixel Coefficients

An Optimized Inversion Method for Hyperspectral Image Fusion Based on a Hue–Intensity–Saturation, Wavelet, and Trust-Region Conjugate Gradient Method

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