A survey on image and video stitching

Image/video stitching is a technology for solving the field of view(FOV)limitation of images/videos.It stitches multiple overlapping images/videos to generate a wide-FOV image/video,and has been used in various fields such as sports broadcasting,video surveillance,street view,and entertainment.This survey reviews image/video stitching algorithms,with a particular focus on those developed in recent years.Image stitching first calculates the corresponding relationships between multiple overlapping images,deforms and aligns the matched images,and then blends the aligned images to generate a wide-FOV image.A seamless method is always adopted to eliminate such potential flaws as ghosting and blurring caused by parallax or objects moving across the overlapping regions.Video stitching is the further extension of image stitching.It usually stitches selected frames of original videos to generate a stitching template by performing image stitching algorithms,and the subsequent frames can then be stitched according to the template.Video stitching is more complicated with moving objects or violent camera movement,because these factors introduce jitter,shakiness,ghosting,and blurring.Foreground detection technique is usually combined into stitching to eliminate ghosting and blurring,while video stabilization algorithms are adopted to solve the jitter and shakiness.This paper further discusses panoramic stitching as a special-extension of image/video stitching.Panoramic stitching is currently the most widely used application in stitching.This survey reviews the latest image/video stitching methods,and introduces the fundamental principles/advantages/weaknesses of image/video stitching algorithms.Image/video stitching faces long-term challenges such as wide baseline,large parallax,and low-texture problem in the overlapping region.New technologies may present new opportunities to address these issues,such as deep learning-based semantic correspondence,and 3D image stitching.Finally,this survey discusses the challenges of image/video stitching and proposes potential solutions.

Research on Stitching Algorithm Based on Tree Branch Image

Branch identification technology is a key technology to achieve automated pruning of fruit tree branches, and one of its technical bottlenecks lies in the stitching of branch images. To this end, we propose a set of branch image stitching technology algorithms. The algorithm is based on the grey-scale prime centroid method to determine the detection feature points, and uses the coordinate transformation matrix H of the corresponding points of the image to carry out the image geometric transformation, and realises the feature matching through sample comparison and classification methods. The experimental results show that the matched point images are more correct and less time-consuming.

A morphology-stitching method to improve Landsat SLC-off images with stripes

Stripes are artifacts in satellite images caused by various factors such as hardware defects. In some cases, these artifacts are introduced by some mitigating algorithms like Landsat SLC-off （Scan Line Corrector） gap-filling methods of LLHM （Local Linear Histogram Matching） and AWLHM （Adaptive Window Linear Histogram Matching）, which leave stripes as a byproduct. To improve Landsat SLC-off images with stripes,we propose an algorithm involving some hypothetical stripe-crossing stitch lines using the mean pixel value of the stitch lines.

Underwater Terrain Image Stitching Based on Spatial Gradient Feature Block

At present,underwater terrain images are all strip-shaped small fragment images preprocessed by the side-scan sonar imaging system.However,the processed underwater terrain images have inconspicuous and few feature points.In order to better realize the stitching of underwater terrain images and solve the problems of slow traditional image stitching speed,we proposed an improved algorithm for underwater terrain image stitching based on spatial gradient feature block.First,the spatial gradient fuzzy C-Means algorithm is used to divide the underwater terrain image into feature blocks with the fusion of spatial gradient information.The accelerated-KAZE(AKAZE)algorithm is used to combine the feature block information to match the reference image and the target image.Then,the random sample consensus(RANSAC)is applied to optimize the matching results.Finally,image fusion is performed with the global homography and the optimal seam-line method to improve the accuracy of image overlay fusion.The experimental results show that the proposed method in this paper effectively divides images into feature blocks by combining spatial information and gradient information,which not only solves the problem of stitching failure of underwater terrain images due to unobvious features,and further reduces the sensitivity to noise,but also effectively reduces the iterative calculation in the feature point matching process of the traditional method,and improves the stitching speed.Ghosting and shape warping are significantly eliminated by re-optimizing the overlap of the image.

Efficient Image Stitching in the Presence of Dynamic Objects and Structure Misalignment

This paper presents a new method for simultaneously eliminating visual artifacts caused by moving objects and structure misalignment in image stitching. Given that the input images are roughly aligned, our approach is implemented in two stages. In the first stage, we discover motions between input images, and then extract their corresponding regions through a multi-seed based region growing algorithm. In the second stage, with prior information provided by the extracted regions, we perform a graph cut optimization in gradient-domain to determine which pixels to use from each image to achieve seamless stitching. Our method is simple to implement and effective. The experimental results illustrate that the proposed approach can produce comparable or superior results in comparison with state-of-the-art methods.

DYNAMICS OF THE LOOPER DRIVE MECHANISM ON A BLIND STITCHING MACHINE

The looper drive mechanism is a main moving part in the blind stitching machine, which is aspatial 5 bar RRRSR linkage. In this paper, a dynamic analysis of the looper drive mechanism is made by means of the ma-trix method. Two methods are adopted in the calculation of the shaking force and shaking moment, one isdone by the constraint reaction of the flame-connected kinematic parts; the other is the inertialforces of all moving links.

Fabricating a smart clothing system based on strain-sensing yarn and novel stitching technology for health monitoring

Various yarn-shaped flexible strain sensors have recently been developed.However,research is lacking on additive manufacturing for smart clothing for integrating yarn sensors with commercial garments.Herein,a strain-sensing yarn is sewn into a piece of fabric through a novel stitching technique,and the influence of the stitching method and needle pitch on the sensing performance is investigated using finite element analysis(FEA).The sensing performance could be improved when the sensing yarn is self-locked in the fabric at the needle eyes,and the needle pitch was reduced to 0.5 cm,which is attributed to the enhanced stress and strain concentration.Meanwhile,the composite sensing fabric featured outstanding performance,including a low detection limit(0.1%),rapid response(280 ms),excellent durability(10000 cycles),and high stability(negligible drift and frequency independence).In addition,the remarkable wear resistance,washability,and anti-interference to ambient humidity and perspiration were obtained.Therein,the optimal stitch trace lengths of sensing yarn for detecting elbow motion,breathing,and heartbeats are discussed.Finally,a smart clothing system composed of smart clothing,data acquisition unit,and mobile APP was developed to simultaneously detect human movement and physiological signals.This work provides a reference to produce intelligent garments based on yarn sensors for health monitoring.

Unsupervised Oral Endoscope Image Stitching Algorithm

Oral endoscope image stitching algorithm is studied to obtain wide-field oral images through regis-tration and stitching,which is of great significance for auxiliary diagnosis.Compared with natural images,oral images have lower textures and fewer features.However,traditional feature-based image stitching methods rely heavily on feature extraction quality,often showing an unsatisfactory performance when stitching images with few features.Moreover,due to the hand-held shooting,there are large depth and perspective disparities between the captured images,which also pose a challenge to image stitching.To overcome the above problems,we propose an unsupervised oral endoscope image stitching algorithm based on the extraction of overlapping regions and the loss of deep features.In the registration stage,we extract the overlapping region of the input images by sketching polygon intersection for feature points screening and estimate homography from coarse to fine on a three-layer feature pyramid structure.Moreover,we calculate loss using deep features instead of pixel values to emphasize the importance of depth disparities in homography estimation.Finally,we reconstruct the stitched images from feature to pixel,which can eliminate artifacts caused by large parallax.Our method is compared with both feature-based and previous deep-based methods on the UDIS-D dataset and our oral endoscopy image dataset.The experimental results show that our algorithm can achieve higher homography estimation accuracy,and better visual quality,and can be effectively applied to oral endoscope image stitching.

Efficient Unsupervised Image Stitching Using Attention Mechanism with Deep Homography Estimation

Traditional feature-based image stitching techniques often encounter obstacles when dealing with images lackingunique attributes or suffering from quality degradation. The scarcity of annotated datasets in real-life scenesseverely undermines the reliability of supervised learning methods in image stitching. Furthermore, existing deeplearning architectures designed for image stitching are often too bulky to be deployed on mobile and peripheralcomputing devices. To address these challenges, this study proposes a novel unsupervised image stitching methodbased on the YOLOv8 (You Only Look Once version 8) framework that introduces deep homography networksand attentionmechanisms. Themethodology is partitioned into three distinct stages. The initial stage combines theattention mechanism with a pooling pyramid model to enhance the detection and recognition of compact objectsin images, the task of the deep homography networks module is to estimate the global homography of the inputimages consideringmultiple viewpoints. The second stage involves preliminary stitching of the masks generated inthe initial stage and further enhancement through weighted computation to eliminate common stitching artifacts.The final stage is characterized by adaptive reconstruction and careful refinement of the initial stitching results.Comprehensive experiments acrossmultiple datasets are executed tometiculously assess the proposed model. Ourmethod’s Peak Signal-to-Noise Ratio (PSNR) and Structure Similarity Index Measure (SSIM) improved by 10.6%and 6%. These experimental results confirm the efficacy and utility of the presented model in this paper.

High precision mode of subaperture stitching for optical surfaces measurement

Subaperture stitching （SAS） provides us with an attractive way of extending the effective aperture and dynamic range of phase measuring interferometers. Accuracy of stitching algorithm becomes the key factor in the SAS technology. In this paper, the basic principle of SAS was introduced and four modes of SAS were discussed. The stitching experiments were done through the SSI-300 workstation designed and developed indepen- dently. There were several comparisons between the four different stitching methods and the measurement of full aperture. The results suggest that the global error averaging mode with reference of subaperture near optic axis is of high precision.

Tensile Mechanical Behavior and Failure Mechanism of a Plain-Woven SiCf/SiC Composites at Room and Elevated Temperatures

Ceramic matrix composites (CMCs) are the preferred materials for solving advanced aerospace high-temperature structural components;it has the comprehensive advantages of higher temperature (~1500˚C) and low density. In service environments, CMCs exhibit complex damage mechanisms and failure modes, which are affected by constituent materials, meso-architecture and inhere defects. In this paper, the in-plane tensile mechanical behavior of a plain-woven SiCf/SiC composite at room and elevated temperatures was investigated, and the factors affecting the tensile strength of the material were discussed in depth. The results show that the tensile modulus and strength of SiCf/SiC composites at high temperature are lower, but the fracture strain increases and the toughness of the composites is enhanced;the stitching holes significantly weaken the tensile strength of the material, resulting in the material is easy to break at the cross-section with stitching holes.

Effect of Stitching on Plain and Open-hole Strength of CFRP Laminates

Experimental and analytical investigation is conducted to explore the effects of stitching on plain （without hole） and open-hole compressive and tensile strength of uniweave T300/QY9512 laminates under different environmental conditions （20 ℃/dry and wet, 150 ℃/dry and wet）. Strength performance of stitched composite laminates is also studied using finite element analysis （FEA） model and compared with the experimental results to validate the model. It is found that under similar environmental conditions, the open-hole compressive strength of stitched laminate is decreased and open-hole tensile strength increased as compared to the unstitched laminates. Predicted tensile and compressive strengths are found to be in a good agreement with the test results and the relative error in all cases is less than 15%.

Automatic Seamless Stitching Method for CCD Images of Chang’E-1 Lunar Mission

A novel automatic seamless stitching method is presented. Compared to the traditional method, it can speed the processing and minimize the utilization of human resources to produce global lunar map. Meanwhile, a new global image map of the Moon with spatial resolution of -120 m has been completed by the proposed method from Chang＇E-1 CCD image data.

Stitching algorithm for ion beam figuring of optical mirrors

A novel stitching machining method for ion beam figuring of optical mirrors is presented in this paper. Problems that should be dealt with in the stitching process such as shaping principle,algorithm for dwell time calculation,parameter identification and compensation for positioning errors are discussed. Based on Computer Controlled Optical Surfacing(CCOS)principle,the finite field nonlinear model is deduced from the stitching shaping mechanism;with the superposition property in the model,a modified Richardson-Lucy iterative algorithm is presented to deconvolute the dwell time for the stitching process;the effect of the positioning errors and the removal rate on the machining accuracy and shape is modeled and then the identification and compensation algorithm for these parameters is proposed based on this model.With these studies,shaping theory and algorithm are constructed,and then the stitching process for ion beam figuring comes into being.Figuring experiments are made on planar samples;the process convergence ratio is 10,which is similar to that in full aperture figuring.Theo- retical and experimental studies indicate that the stitching theory and algorithm in the ion beam figuring process presented in this paper are a novel method for fabrication of precision mirrors with lower cost.

Combined application of extended depth of field imaging, image stitching and polarized microscopy techniques in identification of Spatholobus suberectus

Objective:As traditional techniques for microscopic identification of Chinese medicines currently lack objective and high-quality reference images,here we developed a systemic procedure to be used in microscopic identification of Chinese medicines,which would lead to more objective,effective and accurate identification process.Methods:Spatholobi Caulis(Jixueteng in Chinese)was used as the specimen in the development of such procedure.Jixueteng samples were microscopically examined in bright-and dark-field microscopy.Microscopic images were obtained by regular,EDF,and image stitching techniques.Results:The microscopic images of the characteristics in pulverized Jixueteng were captured,thanks to EDF imaging and image stitching techniques which allowed the detailed and full sighting of each characteristic to be obtained simultaneously.Different layers in anatomical transverse section,including cork,phelloderm,cortex,phloem,cambium,xylem and pith,were distinctively observed.Moreover,by comparing images of bright-and dark-field microscopy,birefringent and non-birefringent components could readily be distinguished.Conclusion:With application of the developed procedure,high-definition,panoramic and microscopic images were acquired,which could be used as the reference images for microscopic identification of Chinese medicines.

Automatic Stitching Method for Chang＇E-2 CCD Images of the Moon

The lunar map is a product of primary scientific objectives of lunar exploration. Aiming at the characteristics of the Chang＇E-2 CCD data, an automatic stitching method used for 2C level CCD data from Chang＇E-2 lunar mission is proposed. Combining with the image registration technique and the characteristics of Chang＇E CCD images, the fast method proposed not only can overcome the contradiction of the high spatial resolution of the CCD images and the low positioning accuracy of the location coordinates, but also can speed up the processing and minimize the utilization of human resources to produce lunar mosaic map. Meanwhile, a new lunar map from 70oN to 70oS with spatial resolution of less than 10 m has been completed by the proposed method. Its average relative location accuracy of the adjacent orbits CCD image data is less than 3 pixels.

Recent Situation of Acupuncture and Moxibustion in the Treatment of Stomach Pain with Deficiency and Cold of Spleen and Stomach

Stomachache is one of the most common diseases of digestive system, among which stomach pain of deficiency cold of spleen and stomach is the most common. Acupuncture and moxibustion therapy as an external treatment of traditional Chinese medicine for relieving stomach pain due to deficiency of spleen and stomach, has the advantages of convenient operation, small adverse reactions and remarkable curative effect, which is easy for patients to accept. In this paper, acupuncture and moxibustion therapy such as moxibustion and warm acupuncture therapy for stomach pain of spleen and stomach deficiency cold type is summarized to provide evidence-based basis for clinical treatment of stomach pain of spleen and stomach deficiency cold type.

In-situ stitching interferometric test system for large piano optics

In-situ testing is an ideal technology for improv- ing the precision and efficiency of fabrication. We developed an in-situ subaperture stitching interferometric test system for large piano optics in the workshop environment with high precision and satisfactory repeatability. In this paper, we provide a brief account of this system and the principle ofin- situ subaperture stitching measurement. Several validation tests are presented, which demonstrate that the developed system is capable of realizing in-situ testing. The size of optical flats can be measured is up to 420 mm×780 mm, and repeatability is smaller than 0.03λ. The paper also dis- cusses the necessary requirements for a suitable workshop environment for ensuring that the tests are stable and reliable.

Multi-camera calibration method based on minimizing the difference of reprojection error vectors

In order to achieve a high precision in three-dimensional（3D） multi-camera measurement system, an efficient multi-cameracalibration method is proposed. A stitching method of large scalecalibration targets is deduced, and a fundamental of multi-cameracalibration based on the large scale calibration target is provided.To avoid the shortcomings of the method, the vector differencesof reprojection error with the presence of the constraint conditionof the constant rigid body transformation is modelled, and mini-mized by the Levenberg-Marquardt （LM） method. Results of thesimulation and observation data calibration experiment show thatthe accuracy of the system calibrated by the proposed methodreaches 2 mm when measuring distance section of 20 000 mmand scale section of 7 000 mm × 7 000 mm. Consequently, theproposed method of multi-camera calibration performs better thanthe fundamental in stability. This technique offers a more uniformerror distribution for measuring large scale space.

Automatic video mosaicking algorithm via dynamic key-frame

Automatic video mosaicking is a challenging task in computer vision. Current researches consider either panoramic or mapping tasks on short videos. In this paper, an automatic mosaicking algorithm is proposed for both mapping and panoramic tasks based on the adapted key-frame on videos of any length.The speeded up robust features(SURF) and the grid motion statistic(GMS) algorithm are used for feature extraction and matching between consecutive frames, which are used to compute the transformation. In order to reduce the influence of the accumulated error during image stitching, an evaluation metric is put forward for the transformation matrix. Besides, a self-growth method is employed to stitch the global image for long videos. The algorithm is evaluated by using aerial-view and panoramic videos respectively on the graphic processing unit(GPU) device, which can satisfy the real-time requirement. The experimental results demonstrate that the proposed algorithm is able to achieve a better performance than the state-of-art.