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Journal articles on the topic 'Image Mosaicking'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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1

Tsai, Victor Jung‐Der, and Ying‐Ting Huang. "Automated image mosaicking." Journal of the Chinese Institute of Engineers 28, no. 2 (2005): 329–40. http://dx.doi.org/10.1080/02533839.2005.9670998.

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Kim, H. G., J. H. Son, and T. Kim. "AUTOMATED MOSAICKING OF GEOSTATIONARY OCEAN COLOR IMAGER BY COMBINATION OF SPATIAL AND FREQUENCY MATCHING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2 (May 30, 2018): 495–99. http://dx.doi.org/10.5194/isprs-archives-xlii-2-495-2018.

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In general, image mosaicking is a useful and important processing for handling images with narrow field of view. It is being used widely for images from commercial cameras as well as from aerial and satellite cameras. For mosaicking images with geometric distortion, geometric correction of each image should be performed before combining images. However, automated mosaicking images with geometric distortion is not a trivial task. The goal of this paper is the development of automated mosaicking techniques applicable to handle GOCI images. In this paper, we try to extract tie-points by using spa

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Fan, Fan, Xiaoyu Jiang, Xingpeng Yan, et al. "Holographic Element-Based Effective Perspective Image Segmentation and Mosaicking Holographic Stereogram Printing." Applied Sciences 9, no. 5 (2019): 920. http://dx.doi.org/10.3390/app9050920.

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Effective perspective image segmentation and mosaicking (EPISM) method is an effective holographic stereogram printing method, but a mosaic misplacement of reconstruction image occurred when focusing away from the reconstruction image plane. In this paper, a method known as holographic element-based effective perspective image segmentation and mosaicking is proposed. Holographic element (hogel) correspondence is used in EPISM method as pixel correspondence is used in direct-writing digital holography (DWDH) method to generate effective perspective images segments. The synthetic perspective ima

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Santellani, E., E. Maset, and A. Fusiello. "SEAMLESS IMAGE MOSAICKING VIA SYNCHRONIZATION." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2 (May 28, 2018): 247–54. http://dx.doi.org/10.5194/isprs-annals-iv-2-247-2018.

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This paper proposes an innovative method to create high-quality seamless planar mosaics. The developed pipeline ensures good robustness against many common mosaicking problems (e.g., misalignments, colour distortion, moving objects, parallax) and differs from other works in the literature because a global approach, known as <i>synchronization</i>, is used for image registration and colour correction. To better conceal the mosaic seamlines, images are cut along specific paths, computed using a Voronoi decomposition of the mosaic area and a shortest path algorithm. Results obtained o

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Li, Ming, Deren Li, Bingxuan Guo, Lin Li, Teng Wu, and Weilong Zhang. "Automatic Seam-Line Detection in UAV Remote Sensing Image Mosaicking by Use of Graph Cuts." ISPRS International Journal of Geo-Information 7, no. 9 (2018): 361. http://dx.doi.org/10.3390/ijgi7090361.

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Image mosaicking is one of the key technologies in data processing in the field of computer vision and digital photogrammetry. For the existing problems of seam, pixel aliasing, and ghosting in mosaic images, this paper proposes and implements an optimal seam-line search method based on graph cuts for unmanned aerial vehicle (UAV) remote sensing image mosaicking. This paper first uses a mature and accurate image matching method to register the pre-mosaicked UAV images, and then it marks the source of each pixel in the overlapped area of adjacent images and calculates the energy value contribut

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Zhao, Jianqing, Xiaohu Zhang, Chenxi Gao, et al. "Rapid Mosaicking of Unmanned Aerial Vehicle (UAV) Images for Crop Growth Monitoring Using the SIFT Algorithm." Remote Sensing 11, no. 10 (2019): 1226. http://dx.doi.org/10.3390/rs11101226.

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To improve the efficiency and effectiveness of mosaicking unmanned aerial vehicle (UAV) images, we propose in this paper a rapid mosaicking method based on scale-invariant feature transform (SIFT) for mosaicking UAV images used for crop growth monitoring. The proposed method dynamically sets the appropriate contrast threshold in the difference of Gaussian (DOG) scale-space according to the contrast characteristics of UAV images used for crop growth monitoring. Therefore, this method adjusts and optimizes the number of matched feature point pairs in UAV images and increases the mosaicking effic

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Mehrdad, S., M. Satari, M. Safdary, and P. Moallem. "TOWARD REAL TIME UAVS’ IMAGE MOSAICKING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 6, 2016): 941–46. http://dx.doi.org/10.5194/isprsarchives-xli-b1-941-2016.

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Anyone knows that sudden catastrophes can instantly do great damage. Fast and accurate acquisition of catastrophe information is an essential task for minimize life and property damage. Compared with other ways of catastrophe data acquisition, UAV based platforms can optimize time, cost and accuracy of the data acquisition, as a result UAVs’ data has become the first choice in such condition. In this paper, a novel and fast strategy is proposed for registering and mosaicking of UAVs’ image data. Firstly, imprecise image positions are used to find adjoining frames. Then matching process is done

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Mehrdad, S., M. Satari, M. Safdary, and P. Moallem. "TOWARD REAL TIME UAVS’ IMAGE MOSAICKING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 6, 2016): 941–46. http://dx.doi.org/10.5194/isprs-archives-xli-b1-941-2016.

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Anyone knows that sudden catastrophes can instantly do great damage. Fast and accurate acquisition of catastrophe information is an essential task for minimize life and property damage. Compared with other ways of catastrophe data acquisition, UAV based platforms can optimize time, cost and accuracy of the data acquisition, as a result UAVs’ data has become the first choice in such condition. In this paper, a novel and fast strategy is proposed for registering and mosaicking of UAVs’ image data. Firstly, imprecise image positions are used to find adjoining frames. Then matching process is done

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Kim, Jae-In, Hyun-cheol Kim, and Taejung Kim. "Robust Mosaicking of Lightweight UAV Images Using Hybrid Image Transformation Modeling." Remote Sensing 12, no. 6 (2020): 1002. http://dx.doi.org/10.3390/rs12061002.

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This paper proposes a robust feature-based mosaicking method that can handle images obtained by lightweight unmanned aerial vehicles (UAVs). The imaging geometry of small UAVs can be characterized by unstable flight attitudes and low flight altitudes. These can reduce mosaicking performance by causing insufficient overlaps, tilted images, and biased tiepoint distributions. To solve these problems in the mosaicking process, we introduce the tiepoint area ratio (TAR) as a geometric stability indicator and orthogonality as an image deformation indicator. The proposed method estimates pairwise tra

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Litvinov, Anatoly, and Yoav Y. Schechner. "Radiometric framework for image mosaicking." Journal of the Optical Society of America A 22, no. 5 (2005): 839. http://dx.doi.org/10.1364/josaa.22.000839.

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Kim, J., T. Kim, D. Shin, and S. H. Kim. "ROBUST MOSAICKING OF UAV IMAGES WITH NARROW OVERLAPS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 6, 2016): 879–83. http://dx.doi.org/10.5194/isprsarchives-xli-b1-879-2016.

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This paper considers fast and robust mosaicking of UAV images under a circumstance that each UAV images have very narrow overlaps in-between. Image transformation for image mosaicking consists of two estimations: relative transformations and global transformations. For estimating relative transformations between adjacent images, projective transformation is widely considered. For estimating global transformations, panoramic constraint is widely used. While perspective transformation is a general transformation model in 2D-2D transformation, this may not be optimal with weak stereo geometry suc

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Kim, J., T. Kim, D. Shin, and S. H. Kim. "ROBUST MOSAICKING OF UAV IMAGES WITH NARROW OVERLAPS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 6, 2016): 879–83. http://dx.doi.org/10.5194/isprs-archives-xli-b1-879-2016.

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This paper considers fast and robust mosaicking of UAV images under a circumstance that each UAV images have very narrow overlaps in-between. Image transformation for image mosaicking consists of two estimations: relative transformations and global transformations. For estimating relative transformations between adjacent images, projective transformation is widely considered. For estimating global transformations, panoramic constraint is widely used. While perspective transformation is a general transformation model in 2D-2D transformation, this may not be optimal with weak stereo geometry suc

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Kim, J., and T. Kim. "DEVELOPMENT OF A ROBUST IMAGE MOSAICKING METHOD FOR SMALL UNMANNED AERIAL VEHICLE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W6 (August 23, 2017): 183–88. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w6-183-2017.

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In this paper, a tie-point based image mosaicking method considering imaging characteristics of small UAVs is proposed. Small UAVs can be characterized to have unstable flight trajectory and lower flight height. The proposed method considers the imaging characteristics in image transformation estimation and image blending process. For image transformation estimation, an optimal transformation model is variably applied by using tie-point area ratio. The optimal tie-point area ratio was about 0.3. Mosaicking error was largely decreased by using this tie-point area ratio. For image blending, a co

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Bano, Sophia, Francisco Vasconcelos, Marcel Tella-Amo, et al. "Deep learning-based fetoscopic mosaicking for field-of-view expansion." International Journal of Computer Assisted Radiology and Surgery 15, no. 11 (2020): 1807–16. http://dx.doi.org/10.1007/s11548-020-02242-8.

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Abstract Purpose Fetoscopic laser photocoagulation is a minimally invasive surgical procedure used to treat twin-to-twin transfusion syndrome (TTTS), which involves localization and ablation of abnormal vascular connections on the placenta to regulate the blood flow in both fetuses. This procedure is particularly challenging due to the limited field of view, poor visibility, occasional bleeding, and poor image quality. Fetoscopic mosaicking can help in creating an image with the expanded field of view which could facilitate the clinicians during the TTTS procedure. Methods We propose a deep le

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15

Lin, Huibao. "Dynamic point selection in image mosaicking." Optical Engineering 45, no. 3 (2006): 030501. http://dx.doi.org/10.1117/1.2180794.

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16

Roy, Sujoy. "Region-based image registration for mosaicking." International Journal of Computer Applications in Technology 37, no. 1 (2010): 57. http://dx.doi.org/10.1504/ijcat.2010.030475.

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thra, P. Pavi, K. B. Sri sathya, and M. Akila. "Image Color Correction using Mosaicking Application." International Journal of Engineering Trends and Technology 29, no. 6 (2015): 278–80. http://dx.doi.org/10.14445/22315381/ijett-v29p251.

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Sakai, H., T. Tanaka, S. Ohata, K. Ishii, and T. Ura. "Underwater Image Mosaicking using Underwater Robot." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2004 (2004): 114. http://dx.doi.org/10.1299/jsmermd.2004.114_3.

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Liu, J., H. T. Li, and H. Y. Gu. "A color balancing method for wide range Remote Sensing imagery based on Regionalization." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W4 (June 26, 2015): 103–8. http://dx.doi.org/10.5194/isprsarchives-xl-7-w4-103-2015.

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Quick mosaicking of wide range remote sensing imagery is an important foundation for land resource survey and dynamic monitoring of environment and nature disasters. It is also technically important for basis imagery of geographic information acquiring and geographic information product updating. This paper mainly focuses on one key technique of mosaicking, color balancing for wide range Remote Sensing imagery. Due to huge amount of data, large covering rage, great variety of climate and geographical condition, color balancing for wide range remote sensing imagery is a difficult problem. In th

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Yang, Yichen, and Xuhui Lee. "Four-band Thermal Mosaicking: A New Method to Process Infrared Thermal Imagery of Urban Landscapes from UAV Flights." Remote Sensing 11, no. 11 (2019): 1365. http://dx.doi.org/10.3390/rs11111365.

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Unmanned aerial vehicles (UAVs) support a large array of technological applications and scientific studies due to their ability to collect high-resolution image data. The processing of UAV data requires the use of mosaicking technology, such as structure-from-motion, which combines multiple photos to form a single image mosaic and to construct a 3-D digital model of the measurement target. However, the mosaicking of thermal images is challenging due to low lens resolution and weak contrast in the single thermal band. In this study, a novel method, referred to as four-band thermal mosaicking (F

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Harihar, Sanjeevakumar, and Dr Manjunath R. "Automated Mosaicking of Medical x-ray Images using SIFT Algorithm." Journal of University of Shanghai for Science and Technology 23, no. 05 (2021): 686–93. http://dx.doi.org/10.51201/jusst/21/05182.

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Image registration is a process of joining any number of images that have similar overlapping regions of the same scene in order to make a panoramic image. In the field of medical, multimedia, and image processing applications image registration process stands challenging. The work presented here on medical images can be applicable for long limb operations and scoliosis operations. Traditional x-ray machines produce a single frame of x-ray image containing a portion of the body part, but they can not generate a large view of body x-ray image in a single frame. This problem can be solved by cre

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SELSAM, PETER, WOLFGANG SCHAEPER, KATJA BRINKMANN, and ANDREAS BUERKERT. "ACQUISITION AND AUTOMATED RECTIFICATION OF HIGH-RESOLUTION RGB AND NEAR-IR AERIAL PHOTOGRAPHS TO ESTIMATE PLANT BIOMASS AND SURFACE TOPOGRAPHY IN ARID AGRO-ECOSYSTEMS." Experimental Agriculture 53, no. 1 (2016): 144–57. http://dx.doi.org/10.1017/s0014479716000089.

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SUMMARYIncreasing image resolution and shrinking camera size facilitates easy mounting of digital cameras on Unmanned Aerial Vehicles (UAVs) to collect large amounts of high-resolution aerial photos for soil surface and vegetation monitoring. Major challenges remain geo-referencing of these images, reliable stitching (mosaicking), elimination of geometric image distortions and compensation of limited image quality and high cost of the equipment. In this study, we report upon the design and field-testing of a custom-made, cost-effective mini-UAV allowing the acquisition of RGB and near-IR image

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Zhang, Ning, Shaohua Jin, Gang Bian, Yang Cui, and Liang Chi. "A Mosaic Method for Side-Scan Sonar Strip Images Based on Curvelet Transform and Resolution Constraints." Sensors 21, no. 18 (2021): 6044. http://dx.doi.org/10.3390/s21186044.

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Due to the complex marine environment, side-scan sonar signals are unstable, resulting in random non-rigid distortion in side-scan sonar strip images. To reduce the influence of resolution difference of common areas on strip image mosaicking, we proposed a mosaic method for side-scan sonar strip images based on curvelet transform and resolution constraints. First, image registration was carried out to eliminate dislocation and distortion of the strip images. Then, the resolution vector of the common area in two strip images were calculated, and a resolution model was created. Curvelet transfor

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Choi, Kyoungtaek, Heeseung Choi, Sangyoun Lee, and Jaihie Kim. "Fingerprint Image Mosaicking by Recursive Ridge Mapping." IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 37, no. 5 (2007): 1191–203. http://dx.doi.org/10.1109/tsmcb.2007.907038.

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Li, Xinghua, Ruitao Feng, Xiaobin Guan, Huanfeng Shen, and Liangpei Zhang. "Remote Sensing Image Mosaicking: Achievements and Challenges." IEEE Geoscience and Remote Sensing Magazine 7, no. 4 (2019): 8–22. http://dx.doi.org/10.1109/mgrs.2019.2921780.

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Xie, Renping, Menghan Xia, Jian Yao, and Li Li. "Guided color consistency optimization for image mosaicking." ISPRS Journal of Photogrammetry and Remote Sensing 135 (January 2018): 43–59. http://dx.doi.org/10.1016/j.isprsjprs.2017.11.012.

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Kang, Yifei, Li Pan, Qi Chen, Tong Zhang, Shasha Zhang, and Zhang Liu. "AUTOMATIC MOSAICKING OF SATELLITE IMAGERY CONSIDERING THE CLOUDS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-3 (June 6, 2016): 415–21. http://dx.doi.org/10.5194/isprsannals-iii-3-415-2016.

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With the rapid development of high resolution remote sensing for earth observation technology, satellite imagery is widely used in the fields of resource investigation, environment protection, and agricultural research. Image mosaicking is an important part of satellite imagery production. However, the existence of clouds leads to lots of disadvantages for automatic image mosaicking, mainly in two aspects: 1) Image blurring may be caused during the process of image dodging, 2) Cloudy areas may be passed through by automatically generated seamlines. To address these problems, an automatic mosai

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Kang, Yifei, Li Pan, Qi Chen, Tong Zhang, Shasha Zhang, and Zhang Liu. "AUTOMATIC MOSAICKING OF SATELLITE IMAGERY CONSIDERING THE CLOUDS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-3 (June 6, 2016): 415–21. http://dx.doi.org/10.5194/isprs-annals-iii-3-415-2016.

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With the rapid development of high resolution remote sensing for earth observation technology, satellite imagery is widely used in the fields of resource investigation, environment protection, and agricultural research. Image mosaicking is an important part of satellite imagery production. However, the existence of clouds leads to lots of disadvantages for automatic image mosaicking, mainly in two aspects: 1) Image blurring may be caused during the process of image dodging, 2) Cloudy areas may be passed through by automatically generated seamlines. To address these problems, an automatic mosai

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Xia, Menghan, Jian Yao, Li Li, Renping Xie, and Yahui Liu. "CONSISTENT TONAL CORRECTION FOR MULTI-VIEW REMOTE SENSING IMAGE MOSAICKING." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-3 (June 6, 2016): 423–31. http://dx.doi.org/10.5194/isprs-annals-iii-3-423-2016.

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In this paper, we propose an effective approach for consistent tonal correction of multi-view images during mosaicking. Our method is specifically designed for mosaicking multi-view remote sensing images acquired under different conditions and/or presenting inconsistent tone. To avoid the correlation of three channels in original <i>RGB</i> images, we convert them to an orthogonal color space <i>l</i>&alpha;&beta; in advance. First of all, the tones of sequential images are transferred from an example image reasonably via our improved color transfer algorithm. S

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Xia, Menghan, Jian Yao, Li Li, Renping Xie, and Yahui Liu. "CONSISTENT TONAL CORRECTION FOR MULTI-VIEW REMOTE SENSING IMAGE MOSAICKING." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-3 (June 6, 2016): 423–31. http://dx.doi.org/10.5194/isprsannals-iii-3-423-2016.

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In this paper, we propose an effective approach for consistent tonal correction of multi-view images during mosaicking. Our method is specifically designed for mosaicking multi-view remote sensing images acquired under different conditions and/or presenting inconsistent tone. To avoid the correlation of three channels in original &lt;i&gt;RGB&lt;/i&gt; images, we convert them to an orthogonal color space &lt;i&gt;l&lt;/i&gt;&alpha;&beta; in advance. First of all, the tones of sequential images are transferred from an example image reasonably via our impr

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Yuan, Shenggu, Ke Yang, Xin Li, and Hongyue Cai. "Automatic Seamline Determination for Urban Image Mosaicking Based on Road Probability Map from the D-LinkNet Neural Network." Sensors 20, no. 7 (2020): 1832. http://dx.doi.org/10.3390/s20071832.

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Image mosaicking which is a process of constructing multiple orthoimages into a single seamless composite orthoimage, is one of the key steps for the production of large-scale digital orthophoto maps (DOM). Seamline determination is one of the most difficult technologies in the automatic mosaicking of orthoimages. The seamlines that follow the centerlines of roads where no significant differences exist are beneficial to improve the quality of image mosaicking. Based on this idea, this paper proposes a novel method of seamline determination based on road probability map from the D-LinkNet neura

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Tian, Jianghao, Yulun Wu, Yonghua Cai, Huaitao Fan, and Weidong Yu. "A Novel Mosaic Method for Spaceborne ScanSAR Images Based on Homography Matrix Compensation." Remote Sensing 13, no. 15 (2021): 2866. http://dx.doi.org/10.3390/rs13152866.

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Accurate and efficient image mosaicking is essential for generating wide-range swath images of spaceborne scanning synthetic aperture radar (ScanSAR). However, the existing methods cannot guarantee the accuracy and efficiency of stitching simultaneously, especially when mosaicking multiple large-area images. In this paper, we propose a novel image mosaic method based on homography matrix compensation to solve the mentioned problem. A set of spaceborne ScanSAR images from the Gaofen-3 (GF-3) satellite were selected to test the performance of the new method. First, images are preprocessed by an

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Yang, Zhanlong, Dinggang Shen, and Pew-Thian Yap. "Image mosaicking using SURF features of line segments." PLOS ONE 12, no. 3 (2017): e0173627. http://dx.doi.org/10.1371/journal.pone.0173627.

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Abaspur Kazerouni, Iman, Gerard Dooly, and Daniel Toal. "Underwater Image Enhancement and Mosaicking System Based on A-KAZE Feature Matching." Journal of Marine Science and Engineering 8, no. 6 (2020): 449. http://dx.doi.org/10.3390/jmse8060449.

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Feature extraction and matching is a key component in image stitching and a critical step in advancing image reconstructions, machine vision and robotic perception algorithms. This paper presents a fast and robust underwater image mosaicking system based on (2D)2PCA and A-KAZE key-points extraction and optimal seam-line methods. The system utilizes image enhancement as a preprocessing step to improve quality and allow for greater keyframe extraction and matching performance, leading to better quality mosaicking. The application focus of this paper is underwater imaging and it demonstrates the

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Zhang, Yu Shuang, Shu Xiao Li, and Hong Xing Chang. "Fast Mosaicking Panoramic Images with Parallax Scene from a PTZ Camera." Advanced Materials Research 468-471 (February 2012): 1775–80. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.1775.

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This paper presents a fast panoramic mosaic algorithm from a video sequence with parallax scene taken by a PTZ camera. A new approach that uses a four-step automatic imaging mosaic, based on interest points, is proposed. The four steps are extraction of interest points, finding corresponding points in the stitching images, deriving the spatial transform matrix then image mosaic. In order to reduce the cost of searching best match of feature points, we employ SIFT-16 descriptor and the LMPs descriptor as index . Our method preserves the efficiency and accuracy of image mosaic.

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Tu Jiangang, 涂建刚, 汪辉 Wang Hui, 徐成 Xu Cheng, 鞠进军 Ju Jinjun, and 沈增辉 Shen Zenghui. "Hyperspectral Image Mosaicking Based on Double-Layer Fusion of Image and Data." Laser & Optoelectronics Progress 58, no. 2 (2021): 0210016. http://dx.doi.org/10.3788/lop202158.0210016.

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Ahmed Mohammed, Ahmed Bdr Eldeen, Fang Ming, and Ren Zhengwei. "Color Balance for Panoramic Images." Modern Applied Science 9, no. 13 (2015): 140. http://dx.doi.org/10.5539/mas.v9n13p140.

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<p>Color correction or color balancing in multi-view image stitching is the process of correcting the color<br />differences between neighboring views which arise due to different exposure levels and view angles. This paper<br />concerns the problem of color balance for panoramic images. A new algorithm is presented to create visual<br />normalization by using correlated feature points between adjacent image sequences. After image mosaicking<br />directly, a weighted average method is used to calculate the pixel value of panoramic image Experimental result<br /

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Tjahjadi, Martinus Edwin, Fourry Handoko, and Silvester Sari Sai. "Novel Image Mosaicking of UAV’s Imagery using Collinearity Condition." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 3 (2017): 1188. http://dx.doi.org/10.11591/ijece.v7i3.pp1188-1196.

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This paper presents a preliminary result of ongoing research on unmanned aerial vehicle (UAV) for cooperative mapping to support a large-scale urban city mapping, in Malang, Indonesia. A small UAV can carry an embedded camera which can continuously take pictures of landscapes. A convenient way of monitoring landscape changes might be through accessing a sequence of images. However, since the camera’s field of view is always smaller than human eye’s field of view, the need to combine aerial pictures into a single mosaic is eminent. Through mosaics, a more complete view of the scene can be acces

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Jun Pan, Qinghua Zhou, and Mi Wang. "Seamline Determination Based on Segmentation for Urban Image Mosaicking." IEEE Geoscience and Remote Sensing Letters 11, no. 8 (2014): 1335–39. http://dx.doi.org/10.1109/lgrs.2013.2293197.

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Du, Qian, Nareenart Raksuntorn, Adnan Orduyilmaz, and Lori M. Bruce. "Automatic Registration and Mosaicking for Airborne Multispectral Image Sequences." Photogrammetric Engineering & Remote Sensing 74, no. 2 (2008): 169–81. http://dx.doi.org/10.14358/pers.74.2.169.

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Wang, Dongliang, Youchuan Wan, Jianhua Xiao, Xudong Lai, Wenli Huang, and Jingzhong Xu. "Aerial Image Mosaicking with the Aid of Vector Roads." Photogrammetric Engineering & Remote Sensing 78, no. 11 (2012): 1141–50. http://dx.doi.org/10.14358/pers.78.11.1141.

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Perrot, Romuald, Pascal Bourdon, and David Helbert. "Confidence-based dynamic optimization model for biomedical image mosaicking." Journal of the Optical Society of America A 36, no. 11 (2019): C28. http://dx.doi.org/10.1364/josaa.36.000c28.

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Zhao, Wen Cang, Xiao Xiao Wang, and Dan Qi. "Study on Matching of Image Topology Structure and Application." Applied Mechanics and Materials 740 (March 2015): 702–5. http://dx.doi.org/10.4028/www.scientific.net/amm.740.702.

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Image matching is a very important field of computer vision and image processing. In this paper we proposed a topology model and algorithm based on characteristic points. Firstly, detecting edge and points feature, then making topology model and proving the excellent properties of the model. Finally, using the proposed model in image mosaicking, at last the feasibility of the model and algorithm are confirmed.

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Hyun, C. U., and H. C. Kim. "MOSAICKING VERY-HIGH-RESOLUTION HELICOPTER-BORNE IMAGES ACQUIRED OVER DRIFTING ARCTIC SEA ICE USING COTS SENSORS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1 (September 26, 2018): 211–15. http://dx.doi.org/10.5194/isprs-archives-xlii-1-211-2018.

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<p><strong>Abstract.</strong> In order to observe and record conditions of the sea ice efficiently and specifically during in-situ investigation with the support of icebreaker research vessel (IBRV), the very-high-resolution (VHR) imaging systems have been used in recent past. The VHR images are generally acquired lower altitude than cloud height, therefore, the images can be acquired even in unfavourable weather conditions for optical satellite image acquisition, and can be applied to comparison with various kinds of remote sensing datasets. However, producing mosaicked imag

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Janani, E., Ruby E.D. Kanmani, and S. Sudha. "Acquisition of high resolution geo objects Using image mosaicking techniques." Journal of Hyperspectral Remote Sensing 6 (2016): 125–29. http://dx.doi.org/10.5935/2237-2202.20160013.

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García, Rafael, Xevi Cufí, and Lluís Pacheco. "Image Mosaicking for Estimating the Motion of an Underwater Vehicle." IFAC Proceedings Volumes 33, no. 21 (2000): 147–52. http://dx.doi.org/10.1016/s1474-6670(17)37066-0.

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Oliveira, Miguel, Angel Domingo Sappa, and Vitor Santos. "A Probabilistic Approach for Color Correction in Image Mosaicking Applications." IEEE Transactions on Image Processing 24, no. 2 (2015): 508–23. http://dx.doi.org/10.1109/tip.2014.2375642.

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Li, Zhiyuan, Weiting Kong, Yongzhao Zhan, and Junlei Bi. "A Novel Image Mosaicking Algorithm for Wireless Multimedia Sensor Networks." International Journal of Distributed Sensor Networks 9, no. 10 (2013): 719640. http://dx.doi.org/10.1155/2013/719640.

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Tian, Yumin, Aifeng Sun, Nan Luo, and Yun Gao. "Aerial image mosaicking based on the 6-DoF imaging model." International Journal of Remote Sensing 41, no. 1 (2019): 74–89. http://dx.doi.org/10.1080/01431161.2019.1657602.

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Xu, Quan, Jun Chen, Linbo Luo, Wenping Gong, and Yong Wang. "UAV Image Mosaicking Based on Multiregion Guided Local Projection Deformation." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13 (2020): 3844–55. http://dx.doi.org/10.1109/jstars.2020.3006289.

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