Kayalvizhi.B, Sakthivel.M
This paper presents a simple and efficient color and luminance compensation approach for image sequences to construct panoramic images on mobile devices. In this approach constant compensation co-efficient for adjacent images are computed from the corresponding pixels in the overlapping areas of the adjacent images in the linearized RGB color space. This can smooth color transition between adjacent images in the image sequence globally and reduce cumulative error in the color correction process. Image stitching is used to integrate information from multiple images with overlapping fields of view in order to produce a panoramic view with all the contents fitted into a single frame. Image stitching literature shows that image stitching is still a challenging problem for single and panoramic images. In recent years many algorithms have been proposed widely to tackle image stitching problem. In this paper we present a detail review of all the recent approaches proposed to tackle the image stitching issue. In addition we also discuss the image stitching process. We formulate stitching as a multi-image matching problem, and use constant. Local features to find matches between all of the images. Because of this our method is impervious to the ordering, orientation, scale and lamination of input images. It is also insensible to noise images that are not part of a panorama, and can recognize multiple panoramas in an unordered image dataset.
Panorama, Image stitching, Multiple Constraint Corner Mapping, mobile panorama, photometric consistency, multiband blending.