|
|
|
Geoscience / DTM
|
Linear Feature Extraction From SPOT Panchromatic Imagery
K.D. Parakum Shantha
Surveyor General’s Office
P.O. Box 506, Colombo
Sri Lanka
1.0 Introduction
Effective utilization of the vast amount of data produced by satellite imaging systems requires the use of automatic methods of image handing. The need for automatic and semi-automatic analysis is becoming acute with the increasing use of images for geology, land resource management, cartographic and military application.
In this context, an important step is image segmentation and identification of features in satellite images . A human interpreter can detect boundaries separating regions of different separating regions of different mean intensity. Automatic method rely on local statistics within some comparatively small mask and boundaries are detected by changes in the local statistics.
Sri Lanka is a developing country and it completed topographic maps at scale of 1:50,000 and map revision is the next task. There is a need for more efficient and cost effective methods for labour intensive map revision tasks particularly change detection. Hence, this study focused on the extraction of liner features in SPOT panchromatic imagery.
Therefore, the mutli-stage approach was established in the way that, enhancement of an image, different filtering techniques to extract linear features, visual detection of linear features from monitor screen and feature classification.
2.0 Data
The test area is located in the southern province of Sri Lanka. The cloud free SPOT pachromatic digital data of the test area was used in this study. The data was pre-processed by SPOT image cooperation. It included radiometric calibration and corrections for systematic geometric distortions.
3.0 Data analysis
The data analysis comprised four steps.
- Enhancement of an image.
- Different filtering techniques to extract linear features
- Visual detection of linear features from monitor screen.
- Feature classification.
3.1 Enhancement of SPOT Image.
Image enhancement operations improve the appearance or quality of the digital image. Histogrm equalization method in contrast stretching is employed in this particular application.
The method use the image histogram directly in formulating contrast modification function. The purpose of this method is to level the image histogram as far as possible in order to assign equal number pixels to each integer pixel value. The pixel value transformation is taken
directly from the cumulative frequency. An equalized image have a good spread of contrast and the enhanced image is shown in figure 1.0.
Figure 1 Enhanced Image
|
|
|
|
|
|
|
