Image Stitching Techniques Applied to Plane or 3-D Models: A Review

Abstract

Image stitching is a technique in which multiple overlapping images of the scene are stitched together to generate an image with wide view and high resolution. Image stitching methods can be broadly classified into feature-based methods and deep learning methods. Feature-based methods use manually designed features to establish transformation relationships between multiple images. This technology has played an important role in medical, industrial, military, and other fields. With the rise of deep learning in computer vision, it has also become the mainstream method in the field of image stitching. This paper provides a systematic literature review of image stitching techniques applied on the plane and 3D models for both feature-based and deep learning methods. We divide the stitching methods into two categories, namely mosaic stitching methods for generating stitched plane images and panoramic stitching methods for generating stitched panoramic images. Based on the camera type, it is further divided into pinhole camera plane stitching methods, pinhole camera panoramic stitching methods, fisheye camera panoramic stitching methods, and light field camera plane stitching methods. Extensive search was conducted in ICIP, TIP, ICCV, ECCV, CVPR, BMVC, ICPR, IJCV, AIM, ITS, TPAMI, SIGGRAFH to summarize related image stitching techniques. 89 articles are selected for systematic literature review and are presented in the table. The objective of this systematic literature review is to provide detailed technical progress in image stitching techniques and to identify the research gap in this field.