Research on UAV Image Matching Algorithm Based on Improved AKAZE Feature and VFC Algorithm

Yan, Qianqian; Li, Qianwen; Zhang, Tongkang

doi:10.1109/icsip49896.2020.9339441

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…In the final step, the obtained homography is applied to the second image. For UAV-acquired multispectral images, some researchers suggested aligning final orthorectified images [59], while others advised to align individual images in the dataset before mosaicking, using SIFT [60] or AKAZE [61] for feature detection (AKAZE is very similar to SIFT). Instead of feature detection, a pyramid algorithm based on Enhanced Correlation Coefficient (ECC) [62] is proposed [63].…”

Section: B Brief Description Of the Mostly Used Image Registration Me...mentioning

confidence: 99%

Design and Verification of a Low-Cost Multispectral Camera for Precision Agriculture Application

Barjaktarovic,

Santoni,

Bruzzone

2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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With the rapid increase of the world population, climate changes, and the slow expansion of cultivated areas, only precision agriculture (PA) can provide enough food or resources. PA requires flexible instruments for measuring the spectral signatures of the crops to understand their conditions. Unfortunately, the high initial costs of multispectral cameras reduce the implementation of PA in small farms, which constitute a large portion of arable land in Europe and contribute with social bonds, local know-how, and cultural legacy. With the objective to speed up the use of multispectral imaging, in this paper, we present a novel low-cost imaging device consisting of a multispectral camera with nine bands and a thermal imager, which price is several times lower than commercially available ones. This paper describes the design and the calibration of the imaging device based on the off-the-shelf components: Raspberry Pi, dedicated quad camera kit, thermal core, and multi-band optical filters. The spectral reconstruction accuracy has a high average R 2 score of 0.986. Finally, images from multiple sensors are aligned using phase-only correlation and dense optical flow, providing a method that can be implemented on all platforms. The presented solution is open source, permitting one to modify and expand the capabilities of the described device and adapt to specific needs. Moreover, the device is flexible as the thermal camera can be removed to reduce the total system cost if its usage is not required. Even if its primary application is PA, the proposed solution can be used for other applications.

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Section: B Brief Description Of the Mostly Used Image Registration Me...mentioning

confidence: 99%

Design and Verification of a Low-Cost Multispectral Camera for Precision Agriculture Application

Barjaktarovic,

Santoni,

Bruzzone

2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…Although the stability and matching accuracy of features are improved by both techniques, the color compensation approach adds more noise to the image and increases the processing requirements for subsequent vision tasks. In addition, Yan et al 25 proposed an unmanned aerial vehicle (UAV) image matching method that combines the AKAZE feature detection algorithm and DAISY feature descriptors. The DAISY algorithm calculates the descriptors after the feature detection phase of the AKAZE algorithm.…”

Section: Introductionmentioning

confidence: 99%

Image matching algorithm based on improved AKAZE and Gaussian mixture model

et al. 2023

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.Simultaneous localization and mapping (SLAM) technology has gained popularity as a result of technological advancements, and image matching—the labor-intensive and crucial component of SLAM technology—has emerged as a key area of research. Hence, the purpose of this study is to develop an image matching method based on improved accelerated-KAZE (AKAZE) and Gaussian mixed model (GMM) segmentation to guarantee the successful completion of subsequent vision challenges. (i) For feature extraction and feature description, first, the AKAZE algorithm was used to extract the key points of the gray-scale image, and second, the binary robust independent elementary features (BRIEF) algorithm was used to obtain the descriptors. Introduction of gray-scale prime method and convolution kernel function to enhance the robustness of features in the BRIEF calculation process. (ii) For feature matching, the gray-scale image is pseudocolored, and then all the pixels in its R channel are segmented by GMM, retaining the features in the same segmented region after brute-force matching. The experimental results demonstrate that, in comparison to oriented FAST and rotated BRIEF and AKAZE, the proposed algorithm in this work provides higher matching accuracy for images of different data sets. That is, the matching approach can be used more effectively for subsequent vision tasks.

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Research on UAV Image Matching Algorithm Based on Improved AKAZE Feature and VFC Algorithm

Cited by 2 publications

References 11 publications

Design and Verification of a Low-Cost Multispectral Camera for Precision Agriculture Application

Design and Verification of a Low-Cost Multispectral Camera for Precision Agriculture Application

Image matching algorithm based on improved AKAZE and Gaussian mixture model

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