What is the Difference Between Sampling and Quantization?
🆚 Go to Comparative Table 🆚Sampling and quantization are two key stages in digital image processing that involve converting continuous data into digital form. The main differences between them are:
- Sampling: This process involves digitizing the coordinate values (x, y) of an image. It discretizes the x-axis (time) and determines the spatial resolution of the digitized images. Sampling is typically done prior to the quantization process.
- Quantization: This process involves digitizing the amplitude values of an image. It discretizes the y-axis (amplitude) and determines the number of grey levels in the digitized images. Quantization is done after the sampling process.
In summary, sampling and quantization are essential steps in converting analog signals to digital signals, allowing images to be processed and used in various applications, such as medicine, remote sensing, and digital prototyping.
Comparative Table: Sampling vs Quantization
Here is a table that highlights the differences between sampling and quantization:
| Feature | Sampling | Quantization |
|---|---|---|
| Definition | Digitizing the coordinate values | Digitizing the amplitude values |
| Axis | x-axis (time) is discretized | y-axis (amplitude) is discretized |
| Process Order | Sampling is done prior to the quantization process | Quantization is done after the sampling process |
| Spatial | Determines the spatial resolution of digitized images | Determines the number of grey levels in digitized images |
| Time | Reduces continuous-time to a series of tent poles over time | Reduces continuous amplitude to a continuous series of stair steps |
In summary, sampling and quantization are essential techniques for converting continuous analog signals into digital form. Sampling discretizes the time axis, while quantization discretizes the amplitude axis. Sampling is performed before quantization, and together they determine the spatial resolution and grey levels of digitized images.
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