Comparison between Three Registration Methods in the Case of Non-Georeferenced Close Range of Multispectral Images

Claudio Ignacio Fernández; Ata Haddadi; Brigitte Leblon; Jinfei Wang; Keri Wang

doi:10.3390/rs13030396

Comparison between Three Registration Methods in the Case of Non-Georeferenced Close Range of Multispectral Images

Remote Sensing ◽

10.3390/rs13030396 ◽

2021 ◽

Vol 13 (3) ◽

pp. 396

Author(s):

Claudio Ignacio Fernández ◽

Ata Haddadi ◽

Brigitte Leblon ◽

Jinfei Wang ◽

Keri Wang

Keyword(s):

Image Registration ◽

Detection System ◽

Projective Transformation ◽

Multispectral Images ◽

Affine Transformations ◽

Blue Band ◽

Greenhouse Production ◽

Registration Method ◽

Speeded Up Robust Features ◽

Close Range

Cucumber powdery mildew, which is caused by Podosphaera xanthii, is a major disease that has a significant economic impact in cucumber greenhouse production. It is necessary to develop a non-invasive fast detection system for that disease. Such a system will use multispectral imagery acquired at a close range with a camera attached to a mobile cart’s mechanic extension. This study evaluated three image registration methods applied to non-georeferenced multispectral images acquired at close range over greenhouse cucumber plants with a MicaSense® RedEdge camera. The detection of matching points was performed using Speeded-Up Robust Features (SURF), and outliers matching points were removed using the M-estimator Sample Consensus (MSAC) algorithm. Three geometric transformations (affine, similarity, and projective) were considered in the registration process. For each transformation, we mapped the matching points of the blue, green, red, and NIR band images into the red-edge band space and computed the root mean square error (RMSE in pixel) to estimate the accuracy of each image registration. Our results achieved an RMSE of less than 1 pixel with the similarity and affine transformations and of less than 2 pixels with the projective transformation, whatever the band image. We determined that the best image registration method corresponded to the affine transformation because the RMSE is less than 1 pixel and the RMSEs have a Gaussian distribution for all of the bands, but the blue band.

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Wafer Image Registration Based on Hough Transform

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.333-335.1038 ◽

2013 ◽

Vol 333-335 ◽

pp. 1038-1042

Author(s):

Fei Tao ◽

Ping An Mu ◽

Shu Guang Dai

Keyword(s):

Image Registration ◽

Hough Transform ◽

Simulated Annealing Algorithm ◽

Detection System ◽

Ccd Camera ◽

Matching Effect ◽

Registration Method ◽

Linear Characteristic ◽

Image Edge ◽

Annealing Algorithm

For wafer defects detection system in a certain resolution, CCD camera cannot get the whole wafer image at one-time, which has an influence on the subsequent defect feature extraction. This paper puts forward an image registration method based on geometry features. Firstly, the information of the image edge can be extracted by using an improved edge detection operator, then using Hough transform to extract the horizontal and vertical lines of the information of the image edge. Secondly, using the correlation of linear characteristic to define the registration standards of the image. A new method, simplex-simulated annealing algorithm, is presented to optimize the registration coefficient of the image. Finally the method is tested and evaluated by the matching effect, the results show that it can effectively achieve the automatic wafer image registration and has a good stability.

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An Underwater Image Real-Time Registration Approach Based on SURF

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.437.888 ◽

2013 ◽

Vol 437 ◽

pp. 888-893 ◽

Cited By ~ 1

Author(s):

Chao Li ◽

Yong Jie Pang ◽

Ming Wei Sheng ◽

Hai Huang

Keyword(s):

Image Registration ◽

Real Time ◽

Median Filter ◽

Filter Method ◽

Interest Points ◽

Registration Method ◽

Speeded Up Robust Features ◽

Time Performance ◽

Underwater Image ◽

Image Contrast Enhancement

In order to meet the demands of real-time performance and robustness for underwater image registration, a novel image registration method based on the SURF (Speeded-Up Robust Features) algorithm is proposed. During the image acquisition process, noise was generated inevitably because of many influencing factors such as atmospheric turbulence, camera defocus during image capturing or relative motion between the camera and the object. Firstly, median filter method was involved during the image preprocessing for underwater image contrast enhancement. Secondly, the SURF algorithm was used to obtain the interest points of the reference and registering images, and the nearest neighbor method was applied to search for coarse matching points. To obtain the precise matching points, the dominant orientations of the coarse matching points were used to eliminate the mismatching points. Finally, the precise matching points were adapted to calculate the mapping relationship between the registering and reference images, the bilinear interpolation method was applied to resample the registering image, and then the registered image was obtained. Experimental results indicated that the proposed preprocessing methods obviously enhanced the image quality, and the introduced image registration approach effectively improved the real-time performance and guaranteed the robustness at the same time.

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An Image Registration Method Based upon Information Theorem on Overlapped Region

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.58-60.1985 ◽

2011 ◽

Vol 58-60 ◽

pp. 1985-1989

Author(s):

Yu Chiang Chuang ◽

Shu Kai S. Fan

Keyword(s):

Image Processing ◽

Image Registration ◽

Objective Function ◽

Projective Transformation ◽

Intensity Data ◽

Test Image ◽

Registration Method ◽

Practical Applications ◽

Overlapping Region ◽

Overlapped Region

Digital image and video have been widely applied to many practical applications due to their simple image acquirement. Image registration is an important image processing for integrating information from images. For Image registration, it is intuitive to orientate images by matching corresponding pixels being considered idealistically identical on the overlapping region. Based on this idea, this article proposes an image registration method that applies the information theorem to the corresponding intensity data. An entropy-based objective function is developed upon the histogram of the intensity differences as to evaluate the similarity between images. Intensity differences represent the differences of the corresponding pixels between the referenced and sensed images on the overlapped region. The sensed image is aligned to the referenced image by minimizing the proposed objective function through iteratively updating the parameters of the projective transformation during the optimization process. The experimental results obtained by means of several test image sets illustrate the effectiveness and feasibility of the proposed image registration method.

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An Accurate Image Registration Method Using a Projective Transformation Model

Eighth Mexican International Conference on Current Trends in Computer Science (ENC 2007) ◽

10.1109/enc.2007.27 ◽

2007 ◽

Cited By ~ 2

Author(s):

Felix Calderon ◽

Leonardo Romero

Keyword(s):

Image Registration ◽

Projective Transformation ◽

Transformation Model ◽

Registration Method

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An Accurate Image Registration Method Using a Projective Transformation Model

Eighth Mexican International Conference on Current Trends in Computer Science (ENC 2007) ◽

10.1109/enc.2007.4351426 ◽

2007 ◽

Author(s):

Felix Calderon ◽

Leonardo Romero

Keyword(s):

Image Registration ◽

Projective Transformation ◽

Transformation Model ◽

Registration Method

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Practical Algorithm Design for the FFT-based Robust Image Registration Method

IEEJ Transactions on Industry Applications ◽

10.1541/ieejias.139.22 ◽

2019 ◽

Vol 139 (1) ◽

pp. 22-29

Author(s):

Yoshi Ri ◽

Hiroshi Fujimoto

Keyword(s):

Image Registration ◽

Algorithm Design ◽

Registration Method ◽

Practical Algorithm ◽

Robust Image

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Skeleton model based space image registration method

The 2nd International Conference on Computing and Data Science ◽

10.1145/3448734.3450458 ◽

2021 ◽

Author(s):

Shaoshi Wu ◽

Xueya Liu

Keyword(s):

Image Registration ◽

Registration Method ◽

Skeleton Model ◽

Model Based ◽

Space Image

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Registration and Fusion of Close-Range Multimodal Wheat Images in Field Conditions

Remote Sensing ◽

10.3390/rs13071380 ◽

2021 ◽

Vol 13 (7) ◽

pp. 1380

Author(s):

Sébastien Dandrifosse ◽

Alexis Carlier ◽

Benjamin Dumont ◽

Benoît Mercatoris

Keyword(s):

Accurate Method ◽

Field Conditions ◽

Plant Phenotyping ◽

Average Error ◽

Multiple Sources ◽

Registration Method ◽

Pixel Intensity ◽

Local Distortion ◽

Close Range ◽

Multimodal Images

Multimodal images fusion has the potential to enrich the information gathered by multi-sensor plant phenotyping platforms. Fusion of images from multiple sources is, however, hampered by the technical lock of image registration. The aim of this paper is to provide a solution to the registration and fusion of multimodal wheat images in field conditions and at close range. Eight registration methods were tested on nadir wheat images acquired by a pair of red, green and blue (RGB) cameras, a thermal camera and a multispectral camera array. The most accurate method, relying on a local transformation, aligned the images with an average error of 2 mm but was not reliable for thermal images. More generally, the suggested registration method and the preprocesses necessary before fusion (plant mask erosion, pixel intensity averaging) would depend on the application. As a consequence, the main output of this study was to identify four registration-fusion strategies: (i) the REAL-TIME strategy solely based on the cameras’ positions, (ii) the FAST strategy suitable for all types of images tested, (iii) and (iv) the ACCURATE and HIGHLY ACCURATE strategies handling local distortion but unable to deal with images of very different natures. These suggestions are, however, limited to the methods compared in this study. Further research should investigate how recent cutting-edge registration methods would perform on the specific case of wheat canopy.

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