The Grand Canal of China is the longest ancient canal in the world. It is an astonishingly huge project in the history
of Chinese civilization. However, some sections have already disappeared as the development of society and change of
environment. It can be detected by using very high resolution image. Object-oriented method based on image
segmentation is being actively studied in the high resolution image process and interpretation to extract a variety of
thematic information. It includes two consecutive processes: first the image is subdivided into separated regions
according to the spectral and spatial heterogeneity in the image segmentation process and then the objects are assigned to
a specific class according to the class's detailed description in the image classification process. The result shows that the
object-oriented approach can realize the full potential of the very high resolution image, have higher accuracy compared
with traditional classification and allow quantitative analysis of land use, simplification of Remote Sensing and GIS
integration.
Remote Sensing is the acquisition of information about an object without touching it. Remote sensing data and image analysis are used as major tools in investigating natural formations and man-made structures. Remote sensing techniques have proven to be very useful in the search for archaeological sites. Techniques such as aerial photography, colorinfrared photography, thermal infrared multi-spectral scanning, and radar imaging have successfully been used to locate potential archaeological sites and add questions to known sites. Image fusion, defined by Franklin and Blodgett (1933) as
the computation of three new values for a pixel based on the known relationship between the input data for the location in the image, has been advocated in a large number of papers as a suitable technique to improve the spatial appraisal of an image produced by merging low spatial resolution data with high spatial resolution data. The different images to be fused can come from different sensors of the same basic type or they may come from different types of sensors. The composite image should contain a more useful description of the scene than provided by any of the individual source
images. In our work, the simultaneously acquired SPOT5 multi-spectral images and SPOT5 panchromatic images are collected. First of all, the geometric correction is conducted to all the images with the error less than 0.5 pixels to make sure the high quality of image fusion. Then image fusion in pixel lever is performed and the image fusion quality is assessed by different criteria.
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