The registration and mosaic of digital images remotely sensed
Yang Venjiu
Center for Remote Sensing in Geology,
Minsitry of Geology and Mineral Resources,
29 Institute Road, Beijing, China
Abstract
Three available registration ways of digital images and three methods of control point selection which include: (1) automatic selection of control point between on-line images by using correlation technique, (2) interactive selection of control point between on-line image and off-line map/image, (3) calculation of the coordinate of control point. The digital mosaic processing is carried out based on the registration. The techniques of gray level adjusting; optimum juncture point selecting and gray level smoothing are adopted in the processing. On the mosaicked image the seam is well eliminated. The high quality mosaic image can meet the requirement of the application and research of remote sensing information. A set of computer software for these techniques was developed.
Introduction
The registration and mosaic of digital image are interrelated and independent to each other in processing of remote sensing information. For registration generally the reference image and the one to be corrected are input to the digital image processing system and interactively selecting control point on both images on the system monitor. Based on the control points the spatial transformation model is fitted. The image to be corrected is processed according to the model and the result image that matches to the reference one geometrically is generated. However, as the application of remote sensing technique is getting more and more widespread and profound, but it has still not satisfied the requirement of application and research if only this registration way is used. In this paper, three different registration ways of digital image are presented. After spatial transformation model is defined registration. Therefore, the different methods of control point selection are used for each registration was.
Mosaic of digital images is based on registration of the images. However, since the image to be mosaicked is not acquired simultaneously for a region, the gray levels or hues usually present some charges between the images. It brings about a spurious artificial seam on the mosaic. A digital mosaic technique, which may produce high quality mosaic, is presented in this paper.
Registration of digital images
- Registration of On-Line Images.
This is a common way of registration. The control point pairs of the reference image and the one to be corrected are selected by user on the monitor. Based on the control point pairs the spatial transformation model is fitted. It causes the output image to be congruent with the reference one geometrically.
After spatial transformation model is defined the corrective selection of control point pairs is the only way to improve the registration accuracy. Visual selection is a general and safe method, but it is time consuming and no high accuracy of location. In order to selecting with high accuracy and save time, the automatic selection techniques of control point are adopted in some conditions. The determination of same ground point from images acquired in different time actually is a problem of pattern reorganization. On image, any surface target is a spectral response of surface characteristics. In most cases the same targets are similar or consistent in spectral features. In other words their variation pattern of spectral features relative to the surrounding object are similar or consistent. Therefore, the location of same ground point for different, temporal images is a pattern-matching problem.
The correlation technique is used to locate the same ground points. For a local neighborhood of two images their correlation measurement is defined by following equation:
where f1 is the image to be corrected and f2 is the reference image. (I,j) are indices in a I*J pixel window area W. The window W is located within a M*N pixel searching area S. F1 is the mean of gray level of all pixels in the window W on image 
is the mean of gray level of all pixles in the area with same dimension as the window W within the searching area S on image f2.
User is asked to select a point on the image f1 and the window W is defined, as a neighborhood located with the point as the center. Then the user selects a point arbitrarily near the corresponding position on the image f2 so the searching area S is delimited, which is an area with the point as the center. According to the equation the area S is searched correlatively by the window W. The maximum value of R (m,n) is found out and (m,n) are its coordinates. So that this point and the one selected by the user on the image f1 are as a control point pair. To do this repeatly until enough pairs have been selected to fit the transformation model for image registration. 2
