Preprocessing of Satellite Images

Preprocessing of Satellite Images

Introduction: 

The satellite observations must be aligned from one time to be compared and to be used for the identification of zones and modifications. Pre-processing is the steps needed for this reason.

The geometry and radiometric calibration of pre-processing and speckle filtering for SAR data are included. Geometric calibration, also referred to as orthorectification, corrects terrain relief, and lens irregularities in the viewing angle of the satellite camera, so that images from various sensors can be compared at different times in equal proportion to maps made using the same projection and size. Calibration of the radiometric is important because of the difference in viewing angles and lighting conditions of the same picture.

Image Processing:

In today's world of advanced technology where most remote sensing data are recorded in digital format, virtually all image interpretation and analysis involves some element of digital processing. Digital image processing may involve numerous procedures including formatting and correcting of the data, digital enhancement to facilitate better visual interpretation, or even automated classification of targets and features entirely by computer.

For discussion purposes, most of the common image processing functions available in image analysis systems can be categorized into the following four categories:

• Preprocessing

• Image Enhancement

• Image Transformation

• Image Classification and Analysis

Preprocessing functions involve those operations that are normally required prior to the main data analysis and extraction of information, and are generally grouped as radiometric or geometric corrections. Radiometric corrections include correcting the data for sensor irregularities and unwanted sensor or atmospheric noise, and converting the data so they accurately represent the reflected or emitted radiation measured by the sensor. Geometric corrections include correcting for geometric distortions due to sensor-Earth geometry variations, and conversion of the data to real world coordinates (e.g. latitude and longitude) on the Earth's surface.

Preprocessing Of Satellite Images (Steps)

1. Download the LandSat image files it is available on the UMCP Global Land Cover Facility (GLCF).

2. Compress/Decompress has an option to uncompressed the files from USGS (Unix tar.gz file), and place them in a directory with the file name.

3. Preprocess LandSat Files:

• Open ENVI, and set the ENVI processing environment

File > Preferences > Default Directories tab

4. Convert to Reflectance:

• Calibrate to reflectance (using the Web) (ENVI Help > Preprocessing Utilities.

• Calibrate to reflectance (without Web input). As of this lesson, calibration files were not available from the Web, for downloading into ENVI to process LandSat 5 images.

• Create a Data Cube (“Layer Stacking”) and Rename Data Cube Bands.

5. Image-to-Image Registration.

• Open ENVI

• Image to Image Registration

6. Perform Unsupervised Classification.

• From the ENVI Main Menu GUI, select Classification > Unsupervised > ISODATA

• Select registered LandSat 5 data cube. 

7. Perform Post Classification.

• From the ENVI Main Menu Window, select Classification > Post Classification > Sieve Classes

8. Group Classified Pixels into Land Use Categories.

• Open three windows in ENVI, as below, to begin classification of the LandSat 5 image. 

• In the Display Window, select Tools > Cursor Location Value. This will help to tell which color class is which.

9.  Download and Project Hydrography Data; Create a Project Geodatabase.

• Open ArcCatalog to examine your data, and select the layers to work with.

10. Export LandSat Images from ENVI into the Project Geodatabase.