The superposition display of massive remote sensing images with different projections

Chen Jiansheng Institute of Remote Sensing Applications

Beijing, China

Chen Jingbo Institute of Remote Sensing Applications

Beijing, China

Abstract—With the development of sensor technology, remote sensing technology has entered a new stage, which can provide various remote sensing data quickly and timely. In some basic process of remote sensing image, such as change monitoring, fusion, and correction, superposition display becomes a direct and rapid method, which can evaluate the quality of the work. In order to solve the problem of the slowness during the superposition display of remote sensing images with different projection, this paper presents some solutions, such as read-write technique of remote sensing images, image block technique, cache technique, dynamic re-projection technique; and these techniques are used in our remote sensing images processing platform. Practice shows that these techniques in this paper can better settle the problem of the slowness during the superposition display of remote sensing images with different projections.

Keywords- re-projection; superposition display; block; cache

I. INTRODUCTION With the rapid development of 3S technology, human

beings capability of information processing, transmission and application achieve an unprecedented level. The system including three-dimensional, multi-angle, all-round and all-weather remote sensing data for Earth observation is growing, which characterized by multi-resolution, multi-sensor, multi-band. Then, it is possible to obtain massive remote sensing data. For the remote sensing image process system, In some basic process of remote sensing image, such as change monitoring, fusion, correction,etc. the superposition display is one of the most direct and important means to evaluate the results of image processing. With such large data, a quick superposition display has a very high demand to hardware and software. In the aspect of superposition display, Li Zhong proposed a strategy that divides the image into small pieces during storing the image data into the database; this method has solved the demand of real-time images display in the client [1]. Lu Jingguo also proposed building image blocks strategy for image display and achieved good results [2]. However, they both do not consider the superposition display of massive remote sensing images with different projections. And this function is very necessary in image process. On the basis of the existing work of the predecessors, this paper introduces image block structure and cache technique, and

discusses how to quickly realize the superposition display of remote sensing images with different projections.

II. KEY TECHNIQUE OF SUPERPOSITION DISPLAY

A. Read-write technique of remote sensing images The read-write technique of remote sensing images in our

image process platform is based on Geospatial Data Abstraction Library (GDAL), which can operate a variety of geographic raster data format, including reading, writing, converting, etc. It provides the application with a uniform abstract data type and a uniform interface; Supported data formats include TIFF / GeoTiff, Arc / Info AscII Grid, PCI Geomatics Database File, etc. More than 60 kinds of data formats can be supported. It is an open-source project, so any organization or individual can use it for free. Its performance and stability are verified by ArcGIS 9.2, Feature Data Objects, Google Earth and achieve good results. It supports nearly all common image formats as well as common remote sensing and Geographic Information System (GIS) image formats. It can supports all the common projection modes [3].

B. Block display For the massive remote sensing image process, it’s

obviously unable to load all the image data into memory, only when needed, the required data will be loaded into the memory for process. When massive image data were loaded into the images process system, only a small piece of image can be seen in the window, therefore, in the remote sensing image display, it’s only needed to reload the visible part of the image instead of loading all the images. We will block the image, as shown in the Fig. 1 below.

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Figure 1. Sketch Map of Block Display

Supposing the original image is divided into 16 blocks. In the windows, the visible part only contains six image blocks in the upper right corner. So, in the windows, we only need to load the image block data contained in the visible part of the windows, instead of loading all the images. As relative to the speed of CPU, the read-write speed of the hard disk is very slow; another advantage of building image blocks lies in the fact that image block display can reduce the hard disk read-write times to obtain a faster display speed.

In the aspect of building image blocks, there is no general criteria to follow, we can block the image by arbitrary rules; however, it’s necessary to consider certain practical issues in the application, such as the index, the efficiency, the read-write speed of the hard disk, etc[4]. Irregular blocks will directly affect index building, pyramid construction and index operation. Additionally, too large or too small image block will affect the effectiveness of the system. If the image block is too large, it may result in loading too much redundant data; if the image block is too small, although it can reduce the redundant data, it increases the frequency of hard disk addressing and read-write operations, and it’s not conducive to decrease the total time of the data accessing. Taking the above questions into account, the size of the image block is usually taken the power of 2. The test we have done proved that, the image block of 128X128 sizes is appropriate, for common computer, neither loading too much redundant data, nor causing the frequent access to the hard disk.

C. Cache technique Since the processed objects in the system is massive remote

sensing image, and most of the data is always stored in the hard disk, the block technique has decreased the frequency of the image positioning and accessing, which overcome the too-slow problem of the image display in a certain degree, But it still affects the response speed of the image display if every display operation is required to load from the hard disk. To further speed the image display, we can open an appropriate size of memory buffer as cache, where we can store the image block which first read from the original image, and then copy the corresponding part to the display buffer [5]. The reason for adopting cache technique is: when this cache contains an image block for window display, the system doesn’t have to re-load

that image block from the original image in the hard disk each time, it’s required to calculated the location of the image block copied in the cache and then copy that image block to display buffer, thus it greatly increases the speed of image display. The size of cache directly affects the efficiency of image display, Too small size would inevitably lead to frequent access the original image, too large size is also restricted by the computer memory, and loading large amounts of data into the cache will cause the delay of the computer speed, so the cache size has to be limited, when the size of the space used in the cache exceeds the limited size, the image block first loaded into the cache should be removed to open space for the latest image block. The Fig. 2 below shows the work flow chart of Cache technique.

Figure 2. Flow Chart of Cache Technique

D. Dynamic re-projection technique In the superposition display of massive remote sensing

images, if it can only realize the superposition display of images with the same projection, it will bring a lot of inconvenience to the user. Users certainly hope that the images used can be displayed in the same coordinate system without regarding whether their projection are the same.

Currently there are many popular projection types. In order to achieve the superposition display of the images with different projections, we have to re-project them into a certain kind of projection type. Different projection types have different coordinate system and different Ellipsoid, therefore, when the images with different projections are displayed in the same windows, It is needed to re-project them into the same projection. The re-projection mechanism of this system is based on the projection transformation function of GDAL.

Here are several main classes and their functions in the GDAL used for projection transformation

1) GDALDataset Class: This class represents the image data set, it is also responsible for the georeferencing transform and coordinate system definition of all bands. You can get the size of image by GetRasterXSize() and GetRasterYSize().You can get the projection of the image by GetProjectionRef(..

2) OGRSpatialReference Class: This class represents a OpenGIS Spatial Reference System, and contains methods for converting between this object organization and well known text (WKT) format.You can set the projection of the image by SetProjParm().Even you can be able to set your own projection by editing the projection parameters.

3) OGRCoordinateTransformation Class: This class can provide projection transformation service between different projections.You can re-projection by Transform().There is no need to know how to re-projection between different projections. Providing two projections of the imges to this class is enough

Image Block is also used in dynamic re-projection technique to solve the problem of the slowness of the traditional re-projection method (files to files). Between the windows loading the image block from the cache and the cache loading the image block from the hard disk, we re-project the image block.

In this system, we regard the projection of the first image loaded in the Windows as the target projection, when loading images with other projection in the windows to superposition display; we should convert other projection of the images into target projection.

Here the operation process of dynamic re-projection.

1) According to the image index number, determine the corresponding geographical scope(latitude, longitude) of the image block.

2) According to the geographical scope, get the file coordinates(Line, Column) of the four corner points of the image block in the original image.

3) According to the file coordinates of the four corner points of the image block, obtain the smallest rectangle that contains the image block.

4) Establish a virtual data set whose data is the data of the smallest recangle.

5) Re-project the virtual data set to the target projection , get a virtual data set with target projection.

6) As the data set obtained after re-projection is bigger than the required image block. According to the geographical scope of the image block, obtain the required image block from the data set re-projected.

Here the Figure 3 shows the steps of re-projection:

Figure 3. Sketch Map of Re-projection

III. CONCLUSION The superposition display of the remote sensing image with

different projections has been successfully applied to the image process software written by the author, which can complete rapid display of massive image data, image editing, image re-projection, etc. The configuration of the computer used in the development is as follows: Inter Pentium Dual-Core E2180 CPU, 1G memory, Windows XP Operating system. In the windows display, there is no feeling of waiting time; but also in the superposition display of images with different projections, it can also be completed quickly and the results can be seen instantly.

The following table is the contrast of the time of superposition display using the traditional re-projection method and dynamic re-projection method. Experimental data is Spot5 panchromatic image, the size of the image is 24000X24000, it includes 1 band.

TABLE I. TIME CONTRAST

Type Size Time(s)

Traditional Re-projection 24000X24000 124.73

Dynamic Re-projection

8X8 2.89

128X128 1.35

512X512 3.57

Practice has proved that the dynamic re-projection technique described in this paper is a very suitable method for the superposition display of massive images with different projection. Compared with the traditional re-projection method, dynamic re-projection has the advantages of a fast process speed, which providing a rapid and effective quality monitoring approach for the image process method such as change monitoring, fusion and correction, etc.

[1] Li Zhong, Du Xukui, Li Mei, “Design and Implementation of Remote

Sensing Image Database,” Geomatics and Spatial Information Technology, Vol31,No.3, pp. 44-45, Jun.2008（in Chinese）

[2] Lu Jingguo, Huang Guoman,Yang Minghui, “Fast Access to Large Amounts of Data Using Visual C++,” Science of Surveying and Mapping,Vol27(3),pp.29-32,2000（in Chinese）

[3] Geospatial Data Abstraction Library, http://www.gdal.org/

[4] Song Jianghong, Zhao Zhongming, “Application of Tile and Hierarchy Structure in Massive Image Processing,” Computer Engineering and Applications Vol33,pp.32-34, 2004.（in Chinese）

[5] Zhang Xiaocan, Huang Zhicai, Chen Gang, Jiang Hengxian, Pan Yunle “Rapid Display Technique of Massive Remote Sensing Image,” Journal of Image and Graphics Vol.7(A).No.10. pp.1022-1023, Oct.2002

（in Chinese）

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