A Survey of Registration Techniques in Remote Sensing Images

Dalmiya, C. P.; Dharun, V. S.

doi:10.17485/ijst/2015/v8i26/81048

Cited by 10 publications

(5 citation statements)

References 20 publications

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“…The registration of multimodal images is common in medical 27–30 and remote sensing fields 31–33 . In these application scenarios, sensors are usually static and do not require strict synchronization in image acquisition.…”

Section: Registration Methodsmentioning

confidence: 99%

“…The registration of multimodal images is common in medical [27][28][29][30] and remote sensing fields. [31][32][33] In these application scenarios, sensors are usually static and do not require strict synchronization in image acquisition. Due to the specificity of the metro environment, we cannot build sensing units in each location to passively acquire images of different scenes.…”

Section: Synchronous Acquisitionmentioning

confidence: 99%

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MRSI: A multimodal proximity remote sensing data set for environment perception in rail transit

Chen

Zhu²,

et al. 2021

Int J of Intelligent Sys

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Rail transit is becoming a major mode of rapid urban and intercity passenger and freight transportation, and its safe operation is of great significance in safeguarding people's lives and properties and maintaining social stability. The current scheme of manual hazard monitoring in rail transit still remains potential safety risks. Accurate rail scene understanding is an essential step towards a smart train. Limited by the closeness of railway scenes, not much research has been conducted on the perception and understanding of rail transit. In view of the above, we propose multimodal remote sensing image (MRSI), the first multimodal proximity remote sensing data set for rail scene understanding. MRSI consists of 27k images collected from freight rail and metro following the pixel and box annotations labeled and checked manually. We used a variety of sensing devices mounted on locomotives to record track scenes under different lighting and weather conditions, including straight, curve, and fork during daytime, dusk, and nighttime, as well as under rainy days. We also include an additional infrared thermometer in the metro environment, propose a new image registration method after synchronous acquisition, and thus construct MRSI combining spatial and radiometric properties. With this data set, we can achieve segmentation of the track area and recognition of obstacles by sensing the environment in front of the train, which lead to rail scene understanding. MRSI is publicly available at https://zenodo.org/record/5732905#.YaPIpsdBwdU.

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Section: Registration Methodsmentioning

confidence: 99%

Section: Synchronous Acquisitionmentioning

confidence: 99%

MRSI: A multimodal proximity remote sensing data set for environment perception in rail transit

Chen

Zhu²,

et al. 2021

Int J of Intelligent Sys

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“…Panchromatic picture have low level of determination than multispectral picture, while frequently a multispectral picture will have a lower spatial determination than panchromatic picture. A pan sharpened picture displays a picture fusion of remote detecting satellite pictures: the multispectral and the panchromatic pictures which provide the optimum of both high phantom determination and high spatial determination [22].…”

Section:  Image Pre-processingmentioning

confidence: 99%

A Segmentation Method of Fused Multispectral and Panchromatic Images using Quick Shift Algorithm and Brovey Transform

Vanmathi¹

2019

IJEAT

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Satellite Image Processing has always been a good domain to carry out researches. This is mainly due to the probability of the vast nature of the domain. There are many Image fusions and segmentation methods are available in the area of Satellite Image Processing. The presented research work proposes the image fusion method to inter twined the high determination panchromatic (PAN) picture and the low-determination multispectral picture to gain the multispectral image of high determination. For picture fusion the Brovey transform is used. The derived inter twined picture is granted as an input to the further segmentation process. Segmentation of the image obtained after the fusion is done and the recognition of land, marine, plantation and residential ranges are shown in the picture of the particular location gained from the satellite. For the segmentation of the fused satellite picture the Quick Shift Segmentation clustering technique is used. Utilizing Quick Shift Segmentation on the combined image the various sections can easily be identified as compared to the unprocessed picture gain from the satellite. Scientists utilize Brovey transform to intertwined RGB colour pictures to high determination panchromatic (PAN) pictures. In the proposed work, the main focus is to degrade spectral irregularity and enhancement of spatial data on merging the pictures of satellite Limitation of the current technique of the combination of images for example restricted directionality, shift invariant, absence of the data are amended by using Brovey transformation. The outcomes of the current system are generally unsatisfied. To overcome this Quick Shift Segmentation technique is used with the Brovey transform in the proposed system. The exactness of segmented image is checked with respect to reference information. The fused image segmentation outcomes have been ascertained and it shows that Brovey transform with interaction of Quick Shift Segmentation technique provides more successive outcomes.

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“…Relationship between the parameters and the dataset are not defined intelligently and it was the major drawback of this technique. Dalmiya and Dharun (2015) present a paper for multitemporal image registration. SIFT, MI and HAIRIS techniques may utilized for diverse registration methods for remote sensing images.…”

Section: Introductionmentioning

confidence: 99%

An enhanced back propagation method for change analysis of remote sensing images with adaptive preprocessing

C.P

Santhi

Sathyabama³

2019

European Journal of Remote Sensing

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A Survey of Registration Techniques in Remote Sensing Images

Cited by 10 publications

References 20 publications

MRSI: A multimodal proximity remote sensing data set for environment perception in rail transit

MRSI: A multimodal proximity remote sensing data set for environment perception in rail transit

A Segmentation Method of Fused Multispectral and Panchromatic Images using Quick Shift Algorithm and Brovey Transform

An enhanced back propagation method for change analysis of remote sensing images with adaptive preprocessing

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