1. Experimental purpose

Through display, geometric correction, filtering and color enhancement of ERS-2 satellite single-band radar images, we can experience the reflection of radar microwave remote sensing images on ground objects. Characteristics and differences from visible light images, understand the content of radar image processing, and initially master the basic operating steps of ENVI radar microwave remote sensing image processing, thereby deepening the understanding of the application principles of radar microwave remote sensing to geology.

2. Experimental content

① ERS-2 radar remote sensing image data input, display and output supported by ENVI; ② Radar image correction; ③ Radar image filtering and enhancement processing; ④ Radar image Color synthesis processing; ⑤ Feature identification of ground objects in radar images; ⑥ Comparative analysis of feature differences between radar remote sensing images and optical remote sensing images.

3. Experimental requirements

Preview the relevant knowledge of radar remote sensing imaging theory, understand the technical parameters of ERS-2 radar data, be able to interpret the information reflected on the radar image, and understand the information reflected in ENVI. Open or store information in radar files, initially master several radar image processing operations of the ENVI software Radar module used in this experiment, and write an experiment report.

IV. Technical conditions

①Microcomputer; ②Guilin ERS-2 single-band Image format data; ③ENVI software; ④Photoshop software (ver.6.0 or above) and ACDSee software ( ver.4.0 or above).

5. Experimental steps

1. Open the radar data file

ENVI provides two ways to open the radar data file.

(1) Select "File>Open External File>Radar>Corresponding radar sensor type" in the ENVI main menu bar, and in the pop-up file selection dialog box, select SAR IM P IPXBJG20090217.E2 band data file, (Note: ERS-2 radar images are different from other optical images, and the file format type is E2). ENVI will automatically extract the header information and enter the image bands into the available bands list.

(2) In the ENVl main menu, select "Radar>Open>Prepare Radar File>Corresponding radar sensor type", which can also be opened.

Display information and parameters from radar data in the Available Bands List, including band name; number of rows, samples, and bands; file size; cross format (BSQ, BIL, BIP); data type (word section, integer, etc.); and information such as whether the data has been geographically located.

2. Radar image correction

(1) Geometric precision correction. The geometric correction method of radar images is the same as the processing method of optical remote sensing images, that is, it is also the method of selecting ground control points (GCPs) and creating GCPs files. You can use one of two methods: Image to Map or Image to image to select GCPs. For details, see Experiment 11 and Experiment 12 in this book.

(2) Comes with correction of positioning parameters. Select "Map>Georeference ENVISAT>Georeference ASAR" in the ENVI main menu. "Select ENVISAT File" pops up. Select the radar image and click the OK button. In the "Select Output Projection" dialog box (Figure 35-1), select the projection according to actual needs. mode, output ground control point path and file name.

Figure 35-1 Select output projection settings dialog box

In the "Registration Parameters" dialog box, redefine the parameters according to the needs of the actual situation, select the output path, and save it under a name . The purpose of correction is to give the radar image geographical coordinate positioning information, which is beneficial to subsequent information extraction.

(3) Antenna Pattern Correction. Due to the instrument's antenna receiving array, the radar image has significant distortion perpendicular to the direction of travel. ENVI's antenna array correction function can be used to eliminate this distortion. The average azimuth angle is calculated and plotted to show the average change in the direction of travel. A polynomial function of user-defined degree can be used to eliminate the distortion produced during reception, with optional additive or multiplicative corrections. The antenna array correction operation method is as follows: ◎Select "Radar>Antenna Pattern Correction" in the ENVl main menu, and in the opened "Antenna Pattern Input File" dialog box, select the radar image file.

◎In the opened "Antenna Pattern Correction Parameters" dialog box (Figure 35-2), edit the following parameters.

Range Direction: columns (Samples) or rows (Lines), the recording method can be determined by viewing the header file of the image data;

Correction method (Correction Method): You can choose addition (Additvie) or multiplication (Multiplicative). Multiplication correction is commonly used for radar antenna array distortion correction;

Polynomial Order: The polynomial order can be changed as needed, the maximum order is 5 .

Click "Plot Polynomial" to display a red average graph (Figure 35-3) with a white, selected polynomial fit superimposed on it. The highest degree of the polynomial can be changed as needed. , and plot it again (preferably with a low-order polynomial) so as not to eliminate local changes in the backscattered signal.

After setting the above parameters, select the output path and file name, click the OK button to execute the operation.

Figure 35-2 Antenna array correction parameter window

Figure 35-3 Antenna array correction curve graph

.3 Image enhancement

ENVI includes several adaptive filters that can be used for SAR processing. Adaptive Filters use the standard deviation around each pixel value to calculate a new pixel value. Unlike traditional low-pass smoothing filters, adaptive filters retain the high-frequency information and details of the image while suppressing the transparency of noise. Adaptive Filters include LEE, Frost, Gamma, Kuan, local σ filter to reduce image spots, and Bit Errors filter to eliminate bad pixels.

The adaptive filter can be used to open the corresponding type of filter through "Filters>Adatove>Filter or main menu>Radar>Adaptive Filters>Filter" in the ENVI main menu, as shown in Figure 35-4 shown. Adaptive filters include the following types.

(1) LEE filter: used to smooth the noise data closely related to each image in brightness and additional or multiplied type noise;

(2) Enhance LEE filter: can be used in Reduce speckle noise while maintaining radar image texture information;

(3) Frost filter: can reduce speckle noise while retaining edges;

(4) Enhance Frost filter Gamma filter: can be used to reduce speckle noise while retaining the texture information of radar images;

(5) Gamma filter: can be used to reduce speckle noise while retaining edge information in radar images;

< p>(6) Kuan filter: used to reduce speckle noise while retaining edges in radar images;

(7) Local Sigma filter: can retain details well and effectively reduce Speckle noise, even in low-contrast areas;

(8) Bit Error Filters: Can eliminate "bit-error" noise in images.

Figure 35-4 LEE filter parameter window

4. Synthetic Color Image (Synthetic Color Image)

You can use the "Synthetic Color Image" item to combine a Convert a grayscale image into a color composite image. This transformation is often used to enhance the display of subtle features in large-scale radar data while retaining useful detail. The operation steps are as follows:

Figure 35-5 Synthetic Color Parameter Window

(1) Select "Radar>Synthetic Color Image" in the ENVI main menu, and select "Radar>Synthetic Color Image" in the file selection dialog box. Enter the file and click the OK button.

(2) In the "Synthetic Color Parameters" dialog box (Figure 35-5), enter the high-pass filter (High Pass Kerenl Size) and low-pass filter exchange kernel size (Low Pass Kerenl Size).

(3) Input saturation value (Saturation Value): range from 0 to 1. The larger the value, the darker or purer the image color.

(4) Select the output path and file name, and click the OK button to perform composite color image processing. The processed results will be automatically loaded into the available band list and can be displayed in "Display".

6. Experiment report

(1) Briefly describe the experimental process.

(2) Answer the questions: ① Radar remote sensing has penetration into clouds and ground vegetation. Compare the ERS-2 image of Guilin City obtained in this experiment with the Guilin image obtained in Experiment 2 or Experiment 9. Compare the TM images and look for differences between the characteristics of the two images.

② Compared with the geometric correction of passive remote sensing images, what are the different and new contents of the correction of radar images? ③What are the black and white radar remote sensing image enhancement methods? What are the color radar remote sensing image enhancement methods? ④After becoming familiar with radar image processing, think about the following questions: Regarding the fusion scheme between SAR images, multispectral images, and high-resolution images, does the fused image have the characteristics of high-resolution multispectral penetration?

See Appendix 1 for the experimental report format.