An in Depth Review Paper on Numerous Image Mosaicing Approaches and Techniques

Image mosaicing is one of the most important subjects of research in computer vision at current. Image mocaicing requires the integration of direct techniques and feature based techniques. Direct techniques are found to be very useful for mosaicing large overlapping regions, small translations and rotations while feature based techniques are useful for small overlapping regions. Feature based image mosaicing is a combination of corner detection, corner matching, motion parameters estimation and image stitching.Furthermore, image mosaicing is considered the process of obtaining a wider field-of-view of a scene from a sequence of partial views, which has been an attractive research area because of its wide range of applications, including motion detection, resolution enhancement, monitoring global land usage, and medical imaging. Numerous algorithms for image mosaicing have been proposed over the last two decades.In this paper the authors present a review on different approaches for image mosaicing and the literature over the past few years in the field of image masaicing methodologies. The authors take an overview on the various methods for image mosaicing.This review paper also provides an in depth survey of the existing image mosaicing algorithms by classifying them into several groups. For each group, the fundamental concepts are first clearly explained. Finally this paper also reviews and discusses the strength and weaknesses of all the mosaicing groups

Survey of image-based representations and compression techniques

In this paper, we survey the techniques for image-based rendering (IBR) and for compressing image-based representations. Unlike traditional three-dimensional (3-D) computer graphics, in which 3-D geometry of the scene is known, IBR techniques render novel views directly from input images. IBR techniques can be classified into three categories according to how much geometric information is used: rendering without geometry, rendering with implicit geometry (i.e., correspondence), and rendering with explicit geometry (either with approximate or accurate geometry). We discuss the characteristics of these categories and their representative techniques. IBR techniques demonstrate a surprising diverse range in their extent of use of images and geometry in representing 3-D scenes. We explore the issues in trading off the use of images and geometry by revisiting plenoptic-sampling analysis and the notions of view dependency and geometric proxies. Finally, we highlight compression techniques specifically designed for image-based representations. Such compression techniques are important in making IBR techniques practical.published_or_final_versio

Progressive Refinement Imaging

This paper presents a novel technique for progressive online integration of uncalibrated image sequences with substantial geometric and/or photometric discrepancies into a single, geometrically and photometrically consistent image. Our approach can handle large sets of images, acquired from a nearly planar or infinitely distant scene at different resolutions in object domain and under variable local or global illumination conditions. It allows for efficient user guidance as its progressive nature provides a valid and consistent reconstruction at any moment during the online refinement process. // Our approach avoids global optimization techniques, as commonly used in the field of image refinement, and progressively incorporates new imagery into a dynamically extendable and memory‐efficient Laplacian pyramid. Our image registration process includes a coarse homography and a local refinement stage using optical flow. Photometric consistency is achieved by retaining the photometric intensities given in a reference image, while it is being refined. Globally blurred imagery and local geometric inconsistencies due to, e.g. motion are detected and removed prior to image fusion. // We demonstrate the quality and robustness of our approach using several image and video sequences, including handheld acquisition with mobile phones and zooming sequences with consumer cameras

A virtual reality system using the concentric mosaic: Construction, rendering, and data compression

This paper proposes a new image-based rendering (IBR) technique called "concentric mosaic" for virtual reality applications. IBR using the plenoptic function is an efficient technique for rendering new views of a scene from a collection of sample images previously captured. It provides much better image quality and lower computational requirement for rendering than conventional three-dimensional (3-D) model-building approaches. The concentric mosaic is a 3-D plenoptic function with viewpoints constrained on a plane. Compared with other more sophisticated four-dimensional plenoptic functions such as the light field and the lumigraph, the file size of a concentric mosaic is much smaller. In contrast to a panorama, the concentric mosaic allows users to move freely in a circular region and observe significant parallax and lighting changes without recovering the geometric and photometric scene models. The rendering of concentric mosaics is very efficient, and involves the reordering and interpolating of previously captured slit images in the concentric mosaic. It typically consists of hundreds of high-resolution images which consume a significant amount of storage and bandwidth for transmission. An MPEG-like compression algorithm is therefore proposed in this paper taking into account the access patterns and redundancy of the mosaic images. The compression algorithms of two equivalent representations of the concentric mosaic, namely the multiperspective panoramas and the normal setup sequence, are investigated. A multiresolution representation of concentric mosaics using a nonlinear filter bank is also proposed.published_or_final_versio