Digital Image Stitching And Registration Research

The development of computer graphics, is producing more and more far-reaching impact. Digital image stitching and registration technology as a key link in image processing has become a hot research field of image processing. Digital image registration fairly wide range of applications, such as face recognition, video surveillance image analysis, bank seal identification, medical diagnosis and panorama picture formation etc., has a very popular application, so this area of scientific research has been greatly attention and development.Image stitching and registration technology have accumulated a large number of research results over the years, especially registration technology, as the basis for stitching, related technology have achieved a higher level. The methods of image stitching are mainly region-based and feature-based, Feature-based stitching method, is mainly to find the corresponding feature points between the images, which can be points, edges, curvature and other characteristics,it's quantity of calculation is small, but is not pricise enough. Region-based approach is to compare each pixel directly, as long as time is long enough, you can splice a sufficient precision. Because it is the entire image pixel operations, so computation is particularly large. Registration techniques are mainly divided into basing on the grayscale, feature and decision tree. The most studied is based on gray-scale image registration, this method directly use the gray-scale image registration information, through the pixels on the similarity measure during a global optimization to achieve registration. This registration method is relatively low rate of registration of changes in gray level information is very sensitive to not make full use of gray-scale statistical properties of each point of larger gray-scale reliance on the information. Feature-based image registration methods of study gradually increased, this method first extract the image features, and then use the characteristics of the image registration. Image registration based on the decision-making need to set up an automated expert system model of the vote, and then the decision-making rules based on certain alignment. The study of this approach, there is no breakthrough.This paper is mainly about the technology improvements of image stitching and registration. For image stitching techniques, how to locate a good convergence of overlapping area more accurately and quickly is the embodiment of their algorithm as well as an important indicator of efficiency. Because in the image stitching process, the relatively large part of the time is mainly consumed in looking for the match area. For the time-consuming characteristics in positioning the region-based stitching overlap proposed the use of multi-threading technology, and improved SSDA algorithm to improve the targeting efficiency. Compared with some traditional algorithms, the speed has greatly improved. The improvements in the registration, according to the high registration rate of image trace, as well as the fractal dimension of the image registration do not need to make the edge, contour, texture and other features, for the image which edge, contour, texture information is not rich can also be carried out, this paper put forward a method to improve registration rates in the traditional registration technology on the basis of fractal dimension by adding the image trace technology, furthermore the introduction of noise processing methods, registration time also improved significantly.