Open AccessImage seamless stitching and straightening based on the image block
Author(s) -
Qu Zhong,
Wang Tengfeng,
An Shiquan,
Liu Ling
Publication year - 2018
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2017.1064
Subject(s) - image stitching , scale invariant feature transform , computer vision , artificial intelligence , computer science , image fusion , feature (linguistics) , image registration , distortion (music) , feature detection (computer vision) , block (permutation group theory) , image (mathematics) , image processing , mathematics , geometry , amplifier , computer network , philosophy , linguistics , bandwidth (computing)
Traditional image stitch methods based on feature point detection require long registration time for high resolution images. In the SIFT (scale invariant feature transform) algorithm, it builds difference‐of‐Gaussian by a linear Gauss expansion filter to obtain the feature. SIFT has poor real time. In this study, a novel image registration method based on image block is proposed to make a rough match for the blocked image and fine match in the most similar blocks by taking advantage of the FAST (features from accelerated segment test) algorithm which runs faster. This way can avoid spending a lot of time in the ineffective area, and enhance the precision and efficiency of the feature point. The accumulative error exists in the process of image stitching, so the image stitched by multiple images has wavelike effects, tilt, or distortion. The camera calibration method is utilised to eliminate the tilt and distortion of the image. The algorithm combining the optimal seam and multi‐resolution fusion is adopted to fuse the stitched image and realise seamless stitch of multiple images in order to achieve a seamless image of high resolution. Simulation experimental results show that the stitching method could realise seamless stitching and straightening of multiple images.