The key technique of 3-D GIS is to realize quick and high-quality 3-D visualization, in which 3-D roaming system based on landform plays an important role. However how to increase efficiency of 3-D roaming engine and process a large amount of landform data is a key problem in 3-D landform roaming system and improper process of the problem would result in tremendous consumption of system resources. Therefore it has become the key of 3-D roaming system design that how to realize high-speed process of distributed data for landform DEM (Digital Elevation Model) and high-speed distributed modulation of various 3-D landform data resources. In the paper we improved the basic ant algorithm and designed the modulation strategy of 3-D GIS landform resources based on the improved ant algorithm. By initially
hypothetic road weights σi , the change of the information factors in the original algorithm would transform from ▵τj to ▵τj+σi and the weights was decided by 3-D computative capacity of various nodes in network environment. So during the course of initial phase of task assignment, increasing the resource information factors of high task-accomplishing rate and decreasing ones of low accomplishing rate would make load accomplishing rate approach the same value as quickly as possible, then in the later process of task assignment, the load balanced ability of the system was further improved. Experimental results show by improving ant algorithm, our system not only decreases many disadvantage of the traditional ant algorithm, but also like ants looking for food effectively distributes the complicated landform algorithm to many computers to process cooperatively and gains a satisfying search result.
In this article, we proposed an effective adaptive 2-dimension blind watermarking algorithm based on feature of a remote sensing image. This algorithm exploited a gray image as the watermark, pretreated the watermark image by Arnold confusion and wavelet compression, and embedded it into the selected subband of wavelet transformation domain of the remote sensing image according to neighboring symbol's mean value and odd-even adjugement rule, moreover, detected watermarks without the original remote sensing image. The attack analysis and experimental results show that the watermarking algorithm is transparent and robust, with accurate watermark detecting results and low complexity, and it also has strong robustness against various image attacks such as JPEG lossy compression, median filtering, additive noise, scaling, cropping, rotation, random geometrical attack and Stirmark attack. Furthermore, after embedding watermarks, there is almost no influence on such applications of the remote sensing image as edge detection and image classification.
In order to hide secrete information in remote sensing image, we proposed an algorithm for secrete information hiding which was adaptive to the feature of remote sensing image. Firstly, we segmented and extracted the secrete information in remote sensing image, and made supplement of gray values in the area corresponding with the secrete information and then produced the disguised remote sensing image which was wiped off secrete information. Then we used for reference the idea of digital watermarks and feature of HVS (Human Visual System) and embedded the secrete sub-image imperceptibly and adaptively into the disguised remote sensing image to produce the disguised remote sensing image in which there hid secrete sub-image. In addition, during the course of extracting secrete information and resuming the remote sensing image, this algorithm didn’t need the original remote sensing image and was a blind one. To those algorithms for information hiding, imperceptivity and amount of hidden information are the most important and robustness is less. And experimental results show that this algorithm is not only quite transparent and has a good effect for large amount of secrete information hiding, but also has a strong robustness against such image attacks as JPEG lossy compression, median filtering, noise adding, scaling, cropping and rotation. Furthermore this algorithm has no influence on such applications as edge detection and image classification of the disguised remote sensing image which has been hidden the secrete information.