Image Stitching via Deep Homography Estimation

This electronic document is a report on Image Stitching. Image stitching is the process of creating an image panorama from a given set of images that have some common(overlapping) area in them. Previous researches done on this topic show that there is still a lot of scope for improvement in this field as although we are able to achieve good results but we haven’t really been able to achieve perfection. There are a lot of factors that are to be blamed here. While Stitching Images, there could be many challenges such as images being corrupt by noise and/or presence of parallax in the images. Image Stitching process is divided into 5 major steps: Image Registration, Feature Detection, Feature Matching, Homography Estimation and Image Blending. In this document we are going to discuss the current status of image processing techniques and what are the challenges being faced.

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Feature Coverage Indexes for Dual Homography Estimation in Constructing Panorama Image

Journal of Sensors ◽

10.1155/2016/1350750 ◽

2016 ◽

Vol 2016 ◽

pp. 1-7

Author(s):

Kyungkoo Jun ◽

Sijung Kim

Keyword(s):

Image Sensors ◽

Image Stitching ◽

Feature Points ◽

Feature Detectors ◽

Panoramic Images ◽

Homography Estimation

Enlarged images can be obtained by various methods. Stitching is one of the efficient methods. It can produce panoramic images by stitching adjacent images which contain overlapping regions even though they are obtained through separate image sensors. Images that contain multiple different planes are hard to be stitched together because each plane has a different homography matrix for perspective warping. For this, a dual homography was proposed. However its performance varies depending on feature detectors which are used to find matching feature points between images. In this paper, we propose three feature coverage indexes which evaluate the stitching performance of feature detectors and predict the outcomes of the stitching. We evaluate four well-known feature detectors by the proposed indexes by applying them to the image stitching process and show that the prediction by the index values coincides with the stitching results.

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End-to-End Image Stitching Network via Multi-Homography Estimation

IEEE Signal Processing Letters ◽

10.1109/lsp.2021.3070525 ◽

2021 ◽

pp. 1-1

Author(s):

Dae-Young Song ◽

Gi-Mun Um ◽

Hee Kyung Lee ◽

Donghyeon Cho

Keyword(s):

Image Stitching ◽

Homography Estimation ◽

End To End

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Real Time Panoramic Video in OpenCV using Image Stitching Techniques

International Journal of Computer Sciences and Engineering ◽

10.26438/ijcse/v6si3.184187 ◽

2018 ◽

Vol 06 (03) ◽

pp. 184-187

Author(s):

K. Rajasri ◽

D. Gayathri ◽

Balasundari Ilanthirayan ◽

A. Sundra

Keyword(s):

Real Time ◽

Image Stitching ◽

Panoramic Video ◽

Stitching Techniques

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Image Stitching Algorithms - A Review

Circulation in Computer Science ◽

10.22632/ccs-2016-251-39 ◽

2016 ◽

Vol 1 (2) ◽

pp. 14-18

Author(s):

Srishty Suman ◽

Utkarsh Rastogi ◽

Rajat Tiwari

Keyword(s):

Video Compression ◽

Video Summarization ◽

Video Stabilization ◽

Image Stitching

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.

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