Image Enhancement Techniques

What is the purpose of image enhancement techniques in digital image processing?

• To add more noise to the image

• The purpose of image enhancement techniques in digital image processing is to improve the quality or perception of an image by emphasizing certain features or removing noise.

• To decrease the file size of the image

• To blur the image further

Explain the difference between spatial domain and frequency domain image enhancement techniques.

• Spatial domain techniques work directly on pixel values, while frequency domain techniques involve transforming the image into the frequency domain.

• Spatial domain techniques involve transforming the image into the frequency domain

• Spatial domain techniques use wavelet transforms

• Frequency domain techniques work directly on pixel values

What is histogram equalization and how does it improve image contrast?

• Histogram equalization is a technique used to improve the contrast of an image by redistributing the intensity values.

• Histogram equalization is a method to rotate images by changing the hue

• Histogram equalization is a process to compress images by reducing the resolution

• Histogram equalization is a technique used to blur images by reducing the contrast

Discuss the concept of image sharpening and provide an example of a sharpening filter.

• Laplacian filter

• Median filter

• Gaussian filter

• Sobel filter

How does noise reduction play a role in image enhancement techniques?

• Noise reduction in image enhancement techniques causes distortion

• Noise reduction plays a crucial role in image enhancement by improving image quality through the removal of unwanted noise artifacts.

• Noise reduction has no impact on image enhancement techniques

• Noise reduction enhances image quality by adding more noise

Describe the process of gamma correction and its significance in image enhancement.

• Gamma correction is used to blur images and reduce their quality.

• Gamma correction is significant in image enhancement as it helps in correcting the gamma curve of the display device, compensating for non-linearities in human vision, and ensuring accurate representation of colors and details in the image.

• Gamma correction is a process that distorts colors in images.

• Gamma correction is only relevant for black and white images.

What are the advantages of using spatial filtering for image enhancement?

• Spatial filtering can introduce artifacts in the image

• Spatial filtering can slow down image processing

• Spatial filtering can effectively improve image quality by reducing noise, enhancing edges, and highlighting important features.

• Spatial filtering may result in loss of image details

Explain the concept of edge enhancement and its application in digital image processing.

• Edge enhancement involves reducing the contrast of the image to make edges less prominent.

• Edge enhancement is achieved by convolving the image with a high-pass filter, such as the Laplacian filter, to accentuate the intensity changes across pixels along edges.

• Edge enhancement is achieved by blurring the image to reduce noise.

• Edge enhancement is a process of randomly altering pixel values in the image.

Discuss the role of contrast stretching in improving the visual quality of an image.

• Contrast stretching improves the visual quality of an image by expanding the range of intensity values and enhancing the contrast between different areas.

• Contrast stretching reduces the range of intensity values in an image

• Contrast stretching blurs the details in different areas of an image

• Contrast stretching has no impact on the visual quality of an image

How can image enhancement techniques be used to improve the quality of medical images?

• By adjusting parameters such as brightness, contrast, sharpness, and noise reduction.

• By reducing the resolution

• By changing the color scheme

• By adding motion blur