Improved real-time photogrammetric stitching (original) (raw)
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A Survey on Real Time Image Stitching
Image stitching is an area of research in Computer graphics or computer vision. It is the process that combines multiple images together using various algorithms, techniques to encompass Field Of View(FOV) to create Panoramic view in a single, large high resolution frame using computer software. In recent years many algorithms, techniques are developed to handle challenges in image stitching. The demand of panoramic view is increased in various fields. Super-resolution images with wide angles are created by image stitching used in medical image stitching, photo mosaics with high resolution, satellite photography , Telemedicine and more. This paper represents recent approaches utilized in Image stitching. Finally, challenges in image stitching is alsodiscussed.
Evergreen, 2023
Computer vision techniques for aligning and fusing images have long been employed to create smooth photographic mosaics. These methods have found applications in image stabilization features of camcorders, production of digital maps and satellite images through high-resolution photographic mosaics, and more. This paper introduces a novel method for generating composites from two or more images, with the ability to significantly reduce or eliminate white space when operating with a live connection. By leveraging algorithms such as Scale-Invariant Feature Transform (SIFT), the proposed method enables feature recognition and extraction from captured images, facilitating the removal of white space in live images. Additionally, this work presents a technique that merges live images with real-time camera input to complete missing elements by intelligently manipulating controlled elements in the images. The resulting approach offers a promising solution for real-time image fusion and the seamless integration of live camera feeds, enhancing the visual quality and completeness of the final composite.
Fast stitching of videos captured from freely moving devices by exploiting temporal redundancy
2010
We investigate the problem of efficient panoramic video construction based on time-synchronized input video streams. No additional constraints are imposed regarding the motion of the capturing video cameras. The presented work is, to the best of our knowledge, the first attempt to construct in real-time a panoramic video stream from input video streams captured by freely moving cameras. The main contribution is in proposing an efficient panoramic video construction algorithm that exploits temporal information to avoid solving the stitching problem fully on a frame by frame basis. We provide detailed experimental evaluation of different methodologies that employ previous frames stitching results such as tracking interest points using optical flow and using areas of overlap to limit the search space for interest points. Our results clearly indicate that making use of temporal information in video stitching can achieve a significant reduction in execution time while providing a comparable effectiveness.
Image Stitching Algorithms - A Review
Circulation in Computer Science, 2016
Image stitching is the process of combining two or more images of the same scene as a single larger image. Image stitching is needed in many applications like video stabilization, video summarization, video compression, panorama creation. The effectiveness of image stitching depends on the overlap removal, matching of the intensity of images, the techniques used for blending the image. In this paper, the various techniques devised earlier for the image stitching and their applications in the relative places has been reviewed.
2006
We propose a stitching algorithm for multi-camera environments which allows to concatenate views with differing centers of projection into a single panoramic image. A common trajectory is defined in two source images to be merged. It serves as a cut that allows to stitch them together. Usually, the layout of the cuts does not allow to stitch both images together naively. Thus, two convex combinations of a warped and a canonic coordinate are applied so that both source images fit together at the cutting edge while the inevitable distortion decreases towards the borders of the image to obtain a natural appearance. In this work, we will particularly investigate the side effects of using multiple perspectives for moving images.
An innovative method for stitching the images for panoramic view
An image stitching method panorama gives serious issues with respect to distortion when collaborating long similar sequential images. To solve the distortion enhanced approach is proposed in this work, adding the alteration of the way sequential referred image and adding a head an approach that can calculate the transformation matrix[3] for any image with in the sequence to put for alignment[11] with the referred image with in the same space of coordinate area. Apart from this the enhanced stitching approach selects the next preceding image automatically based on the matched output points with respect to number of SIFT[10] approach. With regular stitching methodology and enhanced stitching[8] methodology , by comparing these two our approach decreases the SIFT features ROI detected area of the referred image. Our practical results shows theenhanced approach cannotonly initiate the efficiency of stitching on image processing and also drastic reduction of thepanoramic distortion[10][14] issues. This resu lts the plain non distorted panoramic image output.
Image Stitching Algorithm: An Optimization between Correlation-Based and Feature-Based Method
Image stitching detects several images of the same scene and then merges those images to generate a single panoramic image. This paper presents a framework to compare different kind of panorama-creation process, such as correlation-based method and feature-based method with a view to develop an optimum panorama. The evaluations are done by comparing the outputs with respect to the original ground truth along with computation time. We have done simulations by applying these two approaches to draw a satisfactory resolution.
A Novel Concept for Smart Camera Image Stitching
CVWW2016, 2016
As panoramic images are widely used in many applications, efficient image stitching methods that provide visually pleasant image mosaics are needed. In this paper we discuss a novel concept for smart camera image stitching based on graph pyramids. For a multi-camera system, the images have to be aligned accordingly to create an image mosaic. Instead of calculating the corresponding transformations centrally, we aim at enabling each camera to individually calculate the transformation of the image it takes. Graph pyramids used for image segmenta-tion provide information about the segmentation process. We analyze how this information can be used to calculate the transformations for image alignment.
An Accurate Algorithm for Automatic Stitching in One Dimension
2010
The paper addresses the issues in accuracy of various image-stitching algorithms used in the industry today on different types of real-time images. Our paper proposes a stitching algorithm for stitching images in one dimension. The most robust image stitching algorithms make use of feature descriptors to achieve invariance to image zoom, rotation and exposure change. The use of invariant feature descriptors in image matching and alignment makes them more accurate and reliable for a variety of images under different realtime conditions. We assess the accuracy of one such industrial tool, [AUTOSTICH], for our dataset and its underlying Scale Invariant Feature Transform (SIFT) descriptors. The tool’s performance is low in certain scenarios. Our proposed automatic stitching process can be broadly divided into 3 stages: Feature Point Extraction, Points Refinement, and Image Transformation & Blending. Our approach builds on the underlying way a casual end-user captures images through came...
Smoothly varying affine stitching
2011
Traditional image stitching using parametric transforms such as homography, only produces perceptually correct composites for planar scenes or parallax free camera motion between source frames. This limits mosaicing to source images taken from the same physical location. In this paper, we introduce a smoothly varying affine stitching field which is flexible enough to handle parallax while retaining the good extrapolation and occlusion handling properties of parametric transforms. Our algorithm which jointly estimates both the stitching field and correspondence, permits the stitching of general motion source images, provided the scenes do not contain abrupt protrusions.