Contrast manipulation in remote sensing is a fundamental image enhancement technique used to improve the visual appearance of remotely sensed data. Its primary goal is to make features within an image more discernible and easier for human interpretation by adjusting the range of brightness values (digital numbers) displayed.
Remote sensing images often contain information where the actual range of recorded digital values is only a small portion of the possible range that a display device can show (e.g., 0-255 for an 8-bit image). This can result in a 'flat' or low-contrast image where subtle details are hidden. Contrast manipulation aims to 'stretch' or redistribute these values across the full dynamic range of the display.
How Linear Contrast Enhancement (Contrast Stretching) Works
One common method of contrast manipulation is Linear Contrast Enhancement, often referred to as contrast stretching. As described in image processing literature:
Linear contrast enhancement, also referred to as a contrast stretching, linearly expands the original digital values of the remotely sensed data into a new distribution. By expanding the original input values of the image, the total range of sensitivity of the display device can be utilized.
In essence, this process involves mapping the original range of digital values in the image to a new, wider range, typically covering the full range of the display (e.g., 0 to 255). This mapping is done linearly, meaning that the relative relationships between values are maintained – equal steps in the original data correspond to equal steps in the new data, just scaled.
- Original Data Range: Imagine an image where pixel values only range from 50 to 150.
- Linear Stretching: A linear stretch might map the value 50 to 0, the value 150 to 255, and all values in between are scaled proportionally (e.g., 100 would map to approximately 128).
- Result: The stretched image now uses the full 0-255 range, making the differences between pixel values more pronounced and the image appear sharper and more detailed.
Why Use Contrast Manipulation?
Improving image contrast is crucial for various remote sensing applications:
- Enhanced Visual Interpretation: Makes it easier to identify and delineate features like roads, buildings, water bodies, and vegetation types.
- Improved Feature Discrimination: Helps distinguish between similar features that may have only slightly different spectral responses.
- Better Input for Further Analysis: Enhanced images can sometimes lead to more accurate results in subsequent automated processes like classification or change detection.
- Utilizing Display Capabilities: Ensures that the information captured by the sensor is effectively displayed, making full use of the monitor's ability to show variations in brightness.
While linear stretching is a fundamental technique, other non-linear methods (like histogram equalization) also exist, each with different ways of redistributing pixel values to achieve specific enhancement goals. However, the core principle of expanding the original data range to improve visibility remains central to all forms of contrast manipulation.
