Panoramic Image Mosaics Research Articles

Panoramic UAV Image Mosaic Method and Its Application in Pavement Paving Temperature Monitoring

The low-altitude technology of unmanned airborne infrared detection system is used to effectively monitor the temperature segregation in the paving stage and realize the temperature uniformity control of asphalt pavement construction. The image mosaic method can splice two images with overlapping areas together to form a panoramic image. In order to solve the problems of long time-consuming and low accuracy of aerial image mosaic algorithm, the low-temperature area of the whole pavement can be obtained quickly and accurately. In this paper, threshold segmentation technology is introduced to convert the image captured by the unmanned aerial vehicle (UAV) into a binary greyscale image so as to compensate for the mosaic error caused by temperature difference. In order to improve the efficiency and accuracy of splicing, a reference plate is used, which can provide enough feature points for splicing. Finally, the image mosaic method proposed in this paper can quickly obtain the image of the whole low-temperature area of the newly paved asphalt pavement, which has practical value and positive significance for the quality control of asphalt pavement.

Research on Image Mosaic Method Based on Fracture Edge Contour of Bone Tag

Damaged edges of bone tag images contain external factors such as impurities and damage, which affect the stitching process and lead to repair errors. Therefore, this paper proposes a stitching method based on image edge position feature matching. The objective is to improve the accuracy of image stitching by matching feature points based on the position of the image edge pixel so as to solve the accurate stitching of broken edge contour. In the first step of this method, the image containing the broken edge is preprocessed by edge detection, and the location of the broken edge pixel is proposed. Secondly, the feature descriptors were calculated to extract the shape and texture information of the feature points on the fracture edge. Finally, the feature points are optimized by minimum correction and image mosaic is carried out. In terms of image stitching, pre-registration is performed by finding the feature descriptors that are most similar to the edge of the optimum fracture surface profile. The matching operator is added to the overlapping region to obtain the corrected image, and the panoramic image mosaic of the image fracture surface is performed. The experimental results show that feature descriptor matching can ensure the integrity of the fracture, improve the matching accuracy, optimize the uneven deformation of the fracture, ensure the quality of image stitching, and reduce the degree of image distortion.

The Development and Realization of Digital Panorama Media Technology Based on VR Technology.

The purpose of this paper is to understand the digital 3D multimedia panoramic visual communication technology based on virtual reality. Firstly, the key concepts and characteristics of virtual reality are introduced, including the development and application of digital three-dimensional panorama technology. Then, according to the theoretical research, some basic knowledge of 3D panoramic image Mosaic is introduced, including camera image modeling, image sharing, and image exchange. Finally, with the development of the virtual tour at the College of Normal University, the hardware of panoramic technology and the demand of panoramic image search have been expanded in the application. The design of panoramic Mosaic, panoramic image generation, and virtual tour school construction considers real-world issues. The innovation of this paper lies in that will be used by SketchUp8.0 software builds the geometry of 3d virtual scene and by the cylindrical panoramic images based on image of building 3 d virtual scene organic unifies in together and makes a panoramic image can be as the change of seasons in the real scene and real-time change, enhance the sense of the reality of the system and user immersive.

Panoramic image mosaic method based on image segmentation and Improved SIFT algorithm

Aiming at the problem of large amount of calculation in extracting image feature points in panoramic image mosaic by SIFT algorithm, a panoramic image mosaic algorithm based on image segmentation and Improved SIFT is proposed in this paper. The algorithm fully considers the characteristics of panoramic image stitching. Firstly, the stitched image is divided into blocks, and the maximum overlapping block of image pairs is extracted by using mutual information. The SIFT key points are extracted by SIFT algorithm, and the dog is filtered before the spatial extreme value detection of SIFT algorithm to eliminate the feature points with small intensity value; When establishing the feature descriptor, the 128 dimension of the original algorithm is reduced to 64 dimensions to reduce the amount of calculation. In the feature point registration process, the feature descriptor is reduced to 32 dimensions, the feature point pairs are roughly extracted by the optimal node first BBF algorithm, and the feature point pairs are registered and screened by RANSAC; Finally, the image transformation matrix is obtained to realize panoramic image mosaic. The experimental results show that the proposed algorithm not only ensures the panoramic mosaic effect, but also extracts the feature points in 11% of the time of the traditional SIFT algorithm, and the feature point registration speed is 27.17% of the traditional SIFT algorithm.

Underwater Image Mosaic Algorithm Based on Improved Image Registration

In order to obtain panoramic images in a low contrast underwater environment, an underwater panoramic image mosaic algorithm based on image enhancement and improved image registration (IIR) was proposed. Firstly, mixed filtering and sigma filtering are used to enhance the contrast of the original image and de-noise the image. Secondly, scale-invariant feature transform (SIFT) is used to detect image feature points. Then, the proposed IIR algorithm is applied to image registration to improve the matching accuracy and reduce the matching time. Finally, the weighted smoothing method is used for image fusion to avoid image seams. The results show that IIR algorithm can effectively improve the registration accuracy, shorten the registration time, and improve the image fusion effect. In the field of cruise research, instruments equipped with imaging systems, such as television capture and deep-drag camera systems, can produce a large number of image or video recordings. This algorithm provides support for fast and accurate underwater image mosaic and has important practical significance.

Image stitching based on angle-consistent warping

Many warping methods for image stitching have been proposed to construct panoramic image mosaics free of artifacts. Existing methods heavily rely on coordinate correspondences between keypoints in stitching, which may not provide adequate constraints for alignment. In this paper, we discover and employ a new constraint — angle correspondences to address the above problem. The angle of a feature point represents the local directional structure of the point, which is an extension to its position and customarily ignored in image stitching. We propose to jointly consider the coordinates as well as the angles in keypoint correspondences. Such a strategy helps to generate a correct warping in the overlapping regions of the stitched image. In addition, we propose a novel constraint — mesh angle preservation to prevent undesired distortion in non-overlapping areas. Experiments in several challenging cases demonstrate that our method yields more accurate results with significantly less artifacts in comparison with state-of-the-art methods.

A Fast Underwater Image Stitching Algorithm with Adaptive Adjustment of Attitude Angle

In underwater image acquisition process, due to the impact of water currents and other disturbances, the movement posture of the underwater machine will be unstable, which could lead to unusual problems such as twisting of underwater image capture. These factors will increase the error rate of feature point matching and lead to the failure of panoramic image mosaic. In this regard, we propose a new, highly applicable underwater image stitching algorithm. Firstly, the posture angle adjustment link is added to the underwater image processing, and the angle deflection problem of the underwater image is effectively improved by using the posture angle information. Secondly, the feature points of underwater images are extracted based on the accelerated robust feature (SURF) algorithm. Then, the reference image is matched with the feature points of the image to be registered, and effective feature point pairs are obtained by screening. Finally, the images are stitched based on OpenCV to obtain a good panoramic image. Afterexperimental analysis and comparison, our method can increase the number of matching feature point pairs between images. In addition, the Euclidean distance is significantly shortened during the matching process, which further makes the matching of feature points more accurate. Our method satisfactorily overcomes the adverse effects of actual underwater operations and has a better application prospect.

Rapid Defect Detection for Spacecraft in Infrared Reconstructed Images Using Image Mosaic Technique

In order to satisfy the real-time and large scale requirement of spacecraft nondestructive testing using optical pulsed thermography, in this research, we propose a novel approach based on image mosaic technique which can create large scale or panoramic image mosaics from a set of ordered infrared reconstruction images with overlapping areas for defect detection. First, infrared reconstruction images are extracted from the original thermal video stream by the ICA method based on the idea of blind source signal processing. Then for this research’s special mosaic object, a fast and accurate registration scheme is proposed. Abundant scale rotation invariant feature points are quickly obtained by using the hybrid feature detector and descriptor. Moreover, the feature matching process is realized by applying two-way FLANN and MSAC, parameters of the geometric transformation matrix are estimated by MSAC, and image mosaic is realized according to the geometric transformation model. The experimental results convinced the validity and efficiency of the proposed method.

VR Panorama Mosaic Algorithm Based on Particle Swarm Optimization and Mutual Information

With the development of science and technology, Virtual Reality (VR) technology is more and more mature, and has been widely used in real life. In particular, the panorama technology in VR enables users to interact with the objects in the virtual environment in a natural way through the establishment of an artificial three-dimensional virtual environment. so as to get a good experience. Although VR technology has got some maturity, in response to the complex environment and increasing market demand, we put forward higher requirements for VR panorama technology. Panoramic mosaic technology has been studied for a long time at domestically and abroad.. Since the concept of image fusion was put forward, image fusion technology has been developed rapidly. However, the development of image mosaic technology still faces some problems to be studied and these problems were solved. Based on the existing research, present study proposes a VR panoramic image mosaic algorithm based on particle swarm optimization.. The proposed algorithm has the advantages of small computation time, fast splicing speed, high splicing quality, and high splicing confidence. This algorithm is based on particle swarm optimization, combined with the advantages of traditional mutual information algorithm, according to the characteristics of virtual reality imaging, a new model is established. After a large number of comparative experiments, it was found thatproposed method significantly improved the ability of feature region block extraction in VR panoramic image mosaic when compared with the traditional method. At the same time of improving the accuracy, the mapping time is shortened by more than 1 / 3, and the mapping efficiency is improved. Present research work is an innovation of virtual reality panoramic technology.

Panoramic Image Mosaics via Distributed Systems Using Color Moments and Local Wavelet-Features

In this paper, an efficient method based on color moments and local wavelet-features is proposed for panoramic image mosaics. Color moments are used to efficiently represent physical quantities of objects in an image. Wavelet can describe a wide variety of image characteristics and is a key component for image-related applications. Therefore, during the feature-extraction stage for panoramic image mosaics, we exploit color moments and wavelet-subband statistics to construct local feature vectors for image-patch representation. With a distributed system of local area network, the proposed mosaics system can achieve an average 295 FPS. Experimental results show that the local wavelet-features are able to produce plausible and satisfactory panoramic images.

Spatial calibration method for master-slave camera based on panoramic image mosaic

The master-slave camera is composed of fish-eye panoramic camera and pan/tilt/zoom (PTZ) camera. The fish-eye panoramic camera is capable of monitoring a wide field of view, whereas the PTZ dome camera has high mobility and zoom ability. In order to achieve precise interaction, a calibration method based on panoramic image mosaic is proposed, which first composes a mosaic image by several PTZ images and then gets the mapping relationships recorded in the look-up table by template matching. So the mapping relationship between the panoramic image and the motion parameter of PTZ camera can be obtained. Experimental results have demonstrated that it can provide an efficient, fast, and automatic method for the calibration of the master-slave camera.

Panoramic Background Image Generation for PTZ Cameras.

Being able to cover a wide range of views, pan-tilt-zoom (PTZ) cameras have been widely deployed in visual surveillance systems. To achieve a global-view perception of a surveillance scene, it is necessary to generate its panoramic background image, which can be used for the subsequent applications such as road segmentation, active tracking, and so on. However, few works have been reported on this problem, partially due to the lack of benchmark dataset and the high complexity of panoramic image generation of PTZ cameras. In this paper, we build, for the first time to our best knowledge, a benchmark PTZ camera dataset with multiple views, and derive a complete set of panoramic transformation formulas for PTZ cameras. We further propose a fast multi-band blending method to address the efficiency issue in panoramic image fusion and mosaicing. Some related panoramic transformations are also developed, such as cylindrical and overlooking transformations. Our proposed approach exhibits impressive accuracy and efficiency in PTZ panorama generation as well as panoramic image mosaicing.

Research on Panoramic Image Mosaic Method Based on Camera Calibration

Research on Panoramic Image Mosaic Method Based on Camera Calibration

Homographic p-norms: Metrics of homographic image transformation

Images often need to be aligned in a single coordinate system, and homography is one of the most efficient geometric models to align images. This paper presents homographic p-norms, scalar metrics of homographic image transformation, and to the best of our knowledge these are the most rigorous definition of scalar metrics quantifying homographic image transformations. We first define a metric between two homography matrices, and show it satisfies metric properties. Then we propose metrics of a single homography matrix for a general planar region, and ones for a usual rectangle image. For use of the proposed metrics, we provide useful homographic 2-norm expressions derived from the definition of the metrics, and compare the approximation errors of the metrics with respect to the exact metric. As a result, the discrete version of the metric obtained by pixel-wise computation is greatly close to the exact metric. The proposed metrics can be applied to evaluation of transformation magnitude, image closeness estimation, evaluation of camera pose difference, selection of image pair in stereo vision, panoramic image mosaic, and deblurring. Experimental results show the efficacy of the proposed metrics.

A New Method of Panoramic Image Mosaic Based on SIFT

When using the traditional SIFT algorithm extracts feature points, whose characteristics are rotation and scale scaling invariance, the problems are that the feature point extracted by the algorithm is too small and the shortages of real time and robustness. This article proposes a new method called Panoramic Image. This method can define the transformation parameters between the images by using the distances between cities to measure the similarity and using RANSAC with SPRT to diminish the mismatching. The consequence of the experiments demonstrates that this method can shorten the time of registration and prompt the matching feature points.

Optimized design of automatic image mosaic

Virtual reality technology has been widely used in the fields of aerospace, robotics remote operation and biology medicine and so on. Panoramic image mosaic is one of the very important parts. Since photographs taken by the ordinary camera may appear distorted, overlapping and tilting, we propose a wide mosaic algorithm used in the projection transformation in this paper. The algorithm first uses the Harris operator to extract corners, adopting the improved corner response function for avoiding the randomness of k value. Then fast RANSAC method is used to match the images approximately, and the cross-correlation method of gray window as the center of feature points is used to the redundant feature points for further exact match. And then it need solve the model transformation parameters between two images according to these corners information and obtain the projection transformation matrix. Finally, the application of image morphing technique is for reconstructing the image having spatial transform, the result of which are carried on stitching seamlessly with another source image. Experimental results show that the algorithm is effective to achieve a good mosaic.

FUSION OF MOBILE LASER SCANNING AND PANORAMIC IMAGES FOR STUDYING RIVER ENVIRONMENT TOPOGRAPHY AND CHANGES

Abstract. In recent years, laser scanning measurements have been widely used to detect topographic and urban features. In this article, we present a method to integrate mobile laser scanning (MLS) data and panoramic images for producing a textured surface model within a fluvial environment. We also describe the use of the textured surface model to characterize and interpret changes caused by high discharges. The accuracy of MLS-based digital terrain models (DTM) and change detection is evaluated by using static terrestrial laser scanning (TLS) measurements as a reference. The laser scanning data was measured with the mobile mapping system developed in co-operation with the Finnish Geodetic Institute and Aalto University. The boat-based system (BoMMS) has been specially developed for fluvial geomorphology and river mapping. We created panoramic image mosaics by combining sequences of digital images. These methods are suitable for collecting detailed data when traditional methods are unable to gather the data needed for fluvial modelling. The paper also presents a process chain for combining these data sources.

IMAGE ACQUISITION CONSTRAINTS FOR PANORAMIC FRAME CAMERA IMAGING

Abstract. The paper describes an approach to quantify the amount of projective error produced by an offset of projection centres in a panoramic imaging workflow. We have limited this research to such panoramic workflows in which several sub-images using planar image sensor are taken and then stitched together as a large panoramic image mosaic. The aim is to simulate how large the offset can be before it introduces significant error to the dataset. The method uses geometrical analysis to calculate the error in various cases. Constraints for shooting distance, focal length and the depth of the area of interest are taken into account. Considering these constraints, it is possible to safely use even poorly calibrated panoramic camera rig with noticeable offset in projection centre locations. The aim is to create datasets suited for photogrammetric reconstruction. Similar constraints can be used also for finding recommended areas from the image planes for automatic feature matching and thus improve stitching of sub-images into full panoramic mosaics. The results are mainly designed to be used with long focal length cameras where the offset of projection centre of sub-images can seem to be significant but on the other hand the shooting distance is also long. We show that in such situations the error introduced by the offset of the projection centres results only in negligible error when stitching a metric panorama. Even if the main use of the results is with cameras of long focal length, they are feasible for all focal lengths.

Bionic Mosaic Method of Panoramic Image Based on Compound Eye of Fly

To satisfy the requirements of real-time and high quality mosaics, a bionic compound eye visual system was designed by simulating the visual mechanism of a fly compound eye. Several CCD cameras were used in this system to imitate the small eyes of a compound eye. Based on the optical analysis of this system, a direct panoramic image mosaic algorithm was proposed. Several sub-images were collected by the bionic compound eye visual system, and then the system obtained the overlapping proportions of these sub-images and cut the overlap sections of the neighboring images. Thus, a panoramic image with a large field of view was directly mosaicked, which expanded the field and guaranteed the high resolution. The experimental results show that the time consumed by the direct mosaic algorithm is only 2.2% of that by the traditional image mosaic algorithm while guaranteeing mosaic quality. Furthermore, the proposed method effectively solved the problem of misalignment of the mosaic image and eliminated mosaic cracks as a result of the illumination factor and other factors. This method has better real-time properties compared to other methods.

Vignette and Exposure Calibration and Compensation

We discuss calibration and removal of "vignetting" (radial falloff) and exposure (gain) variations from sequences of images. Even when the response curve is known, spatially varying ambiguities prevent us from recovering the vignetting, exposure, and scene radiances uniquely. However, the vignetting and exposure variations can nonetheless be removed from the images without resolving these ambiguities or the previously known scale and gamma ambiguities. Applications include panoramic image mosaics, photometry for material reconstruction, image-based rendering, and preprocessing for correlation-based vision algorithms.