Image Sampling and Quantization

What is the purpose of quantization in image processing?

• Quantization increases the number of distinct colors in an image.

• Quantization in image processing is used to reduce the number of distinct colors in an image.

• Quantization enhances the resolution of an image.

• Quantization is used to blur the edges of an image.

How does the number of quantization levels affect image quality?

• More quantization levels result in higher image quality, while fewer quantization levels lead to lower image quality.

• Fewer quantization levels result in higher image quality, while more quantization levels lead to lower image quality.

• Quantization levels have no impact on image quality.

• Increasing quantization levels decreases image quality, while decreasing quantization levels increases image quality.

Define sampling rate in the context of image processing.

• Sampling rate refers to the color depth of an image

• The sampling rate in image processing is the number of pixels in an image

• The sampling rate in image processing is the number of samples taken per unit of time or space.

• Sampling rate is the resolution of an image

Explain the relationship between sampling rate and image resolution.

• Higher sampling rate leads to lower image resolution.

• Higher sampling rate generally leads to higher image resolution.

• Sampling rate has no impact on image resolution.

• Lower sampling rate results in higher image resolution.

What is the significance of bit depth in digital images?

• Bit depth determines the file format of the image

• Bit depth affects the image resolution

• Bit depth determines the physical size of the image

• Bit depth in digital images determines the color accuracy and quality of the image by specifying the number of bits used to represent each pixel's color.

How does increasing the bit depth impact the color accuracy of an image?

• Increasing the bit depth has no impact on color accuracy.

• Increasing the bit depth improves color accuracy by providing more color shades to represent.

• Increasing the bit depth reduces color accuracy due to oversaturation.

• Increasing the bit depth distorts color accuracy by limiting color range.

What is the difference between quantization levels and bit depth?

• Quantization levels determine the resolution of the signal, while bit depth determines the dynamic range and precision of the signal.

• Quantization levels determine the frequency of the signal, while bit depth determines the color depth of the signal.

• Quantization levels are related to analog signals, while bit depth is related to digital signals.

• Quantization levels refer to the speed of data transmission, while bit depth refers to the size of the data packets.

Why is it important to consider sampling rate when capturing images?

• Sampling rate affects the color balance of images

• Higher sampling rates result in smaller file sizes

• Sampling rate determines the physical size of the camera

• Sampling rate is important when capturing images because it directly impacts the quality and level of detail in the captured images.

Discuss the trade-off between higher quantization levels and file size in images.

• Lower quantization levels provide better color accuracy

• The trade-off between higher quantization levels and file size in images is that higher quantization levels provide better color accuracy and detail but result in larger file sizes, while lower quantization levels reduce file size but may sacrifice color accuracy and detail.

• Higher quantization levels result in smaller file sizes

• Higher quantization levels reduce color accuracy

How does quantization error affect the quality of an image?

• Quantization error has no impact on image quality

• Quantization error improves color accuracy in images

• Quantization error enhances image resolution

• Quantization error degrades the quality of an image by introducing artifacts and reducing color accuracy.