Registration of visible and near infrared unmanned aerial vehicle images based on Fourier-Mellin transform

Rabatel, Gilles; Labbé, Sabrina

doi:10.1007/s11119-016-9437-x

Cited by 23 publications

(18 citation statements)

References 21 publications

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“…A complete description of the aerial mission can be found in Refs. [102,103]. The drones were equipped with two high-resolution cameras (4704 × 3136) mounted on a gimbal system.…”

Section: Service Robotsmentioning

confidence: 99%

Robots in Agriculture: State of Art and Practical Experiences

Roldán¹,

Cerro²,

Garzón‐Ramos³

et al. 2018

Service Robots

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The presence of robots in agriculture has grown significantly in recent years, overcoming some of the challenges and complications of this field. This chapter aims to collect a complete and recent state of the art about the application of robots in agriculture. The work addresses this topic from two perspectives. On the one hand, it involves the disciplines that lead the automation of agriculture, such as precision agriculture and greenhouse farming, and collects the proposals for automatizing tasks like planting and harvesting, environmental monitoring and crop inspection and treatment. On the other hand, it compiles and analyses the robots that are proposed to accomplish these tasks: e.g. manipulators, ground vehicles and aerial robots. Additionally, the chapter reports with more detail some practical experiences about the application of robot teams to crop inspection and treatment in outdoor agriculture, as well as to environmental monitoring in greenhouse farming.

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“…A complete description of the aerial mission can be found in Refs. [102,103]. The drones were equipped with two high-resolution cameras (4704 × 3136) mounted on a gimbal system.…”

Section: Service Robotsmentioning

confidence: 99%

Robots in Agriculture: State of Art and Practical Experiences

Roldán¹,

Cerro²,

Garzón‐Ramos³

et al. 2018

Service Robots

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“…At present, the registration methods for infrared and visible image can be classified into two categories: global region-based methods and local features-based methods. Global region-based methods obtain correspondence by using the whole image content in spatial domain or transform domain, which mainly include mutual information (MI) [8,11,12], phase correlation (PC) [4], Fourier transform [6,13], particle swarm optimization (PSO) [7], gradient information [5,14], and template correlation matching [15,16]. Those methods can get remarkable performance for images with small geometric changes or medical images with high correlation in global intensity.…”

Section: Related Workmentioning

confidence: 99%

“…Second, he various intrinsic and extrinsic sensing conditions may lead to large geometric deformations that exist between the images, which further increase the difficulty of registration. A number of related methods have been proposed and applied successfully in the situation where the geometric changes are small [4][5][6][7][8] or can be greatly alleviated according to the capture information [9,10]. However, automatic infrared and visible image registration has not been solved effectively in complicated environments with large geometric changes and significant differences in contrast.…”

Section: Introductionmentioning

confidence: 99%

A Novel Affine and Contrast Invariant Descriptor for Infrared and Visible Image Registration

Liu

Zhang

et al. 2018

Remote Sensing

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Infrared and visible image registration is a very challenging task due to the large geometric changes and the significant contrast differences caused by the inconsistent capture conditions. To address this problem, this paper proposes a novel affine and contrast invariant descriptor called maximally stable phase congruency (MSPC), which integrates the affine invariant region extraction with the structural features of images organically. First, to achieve the contrast invariance and ensure the significance of features, we detect feature points using moment ranking analysis and extract structural features via merging phase congruency images in multiple orientations. Then, coarse neighborhoods centered on the feature points are obtained based on Log-Gabor filter responses over scales and orientations. Subsequently, the affine invariant regions of feature points are determined by using maximally stable extremal regions. Finally, structural descriptors are constructed from those regions and the registration can be implemented according to the correspondence of the descriptors. The proposed method has been tested on various infrared and visible pairs acquired by different platforms. Experimental results demonstrate that our method outperforms several state-of-the-art methods in terms of robustness and precision with different image data and also show its effectiveness in the application of trajectory tracking.

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“…This procedure was implemented on the Graphics Processing Unit of the BS computer using Compute Unified Device Architecture (CUDA) libraries. A registration accuracy of 0.3 pixels was obtained (Rabatel and Labbé 2016).…”

Section: Remote Perception Systemmentioning

confidence: 99%

Fleets of robots for environmentally-safe pest control in agriculture

Santos

Ribeiro

Fernández‐Quintanilla

et al. 2016

Precision Agric

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176

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Feeding the growing global population requires an annual increase in food production. This requirement suggests an increase in the use of pesticides, which represents an unsustainable chemical load for the environment. To reduce pesticide input and preserve the environment while maintaining the necessary level of food production, the efficiency of relevant processes must be drastically improved. robotic systems for effective weed and pest control aimed at diminishing the use of agricultural chemical inputs, increasing crop quality and improving the health and safety of production operators. To achieve this overall objective, a fleet of heterogeneous ground and aerial robots was developed and equipped with innovative sensors, enhanced endeffectors and improved decision control algorithms to cover a large variety of agricultural situations. This article describes the scientific and technical objectives, challenges and outcomes achieved in three common crops.

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Registration of visible and near infrared unmanned aerial vehicle images based on Fourier-Mellin transform

Cited by 23 publications

References 21 publications

Robots in Agriculture: State of Art and Practical Experiences

Robots in Agriculture: State of Art and Practical Experiences

A Novel Affine and Contrast Invariant Descriptor for Infrared and Visible Image Registration

Fleets of robots for environmentally-safe pest control in agriculture

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