Digital Image Processing

What is image filtering in digital image processing?

• Image filtering involves physically cleaning a printed image

• Image filtering in digital image processing is the process of enhancing or modifying an image by applying a specific mathematical operation to each pixel using a filter kernel.

• Image filtering is the process of converting an image to a different file format

• Image filtering refers to adjusting the brightness of an image

Explain the concept of edge detection and its importance in image processing.

• Edge detection is not important in image processing and can be skipped.

• Edge detection is essential in image processing as it allows for feature extraction, object recognition, and image segmentation by highlighting important boundaries and details within an image.

• Edge detection is only relevant for black and white images, not color images.

• Edge detection is used to blur images and reduce their quality.

How is image segmentation used in digital image processing?

• Image segmentation is used to convert images into text documents

• Image segmentation is used to enhance image quality by adding filters

• Image segmentation is used to create 3D images from 2D images

• Image segmentation is used to partition an image into multiple segments to simplify the representation of an image or to locate objects and boundaries.

What is color correction and why is it essential in image processing?

• Color correction is used to add more colors to an image, making it visually appealing

• Color correction is only necessary for black and white images

• Color correction is a process that removes colors from an image

• Color correction is essential in image processing to ensure accurate and consistent colors, maintaining the true colors of the image and improving overall quality.

Describe the process of feature extraction in digital image processing.

• Feature extraction is the process of compressing images to reduce file size.

• Feature extraction involves converting images into text data.

• Feature extraction is only applicable to black and white images.

• Feature extraction in digital image processing is the process of identifying and extracting important information or features from an image, such as edges, corners, textures, or colors.

What is image compression and why is it necessary in image processing?

• Image compression is used to increase storage space in image processing.

• Image compression is necessary in image processing to save storage space, reduce transmission time, and improve overall performance.

• Image compression is not necessary in image processing as it slows down performance.

• Image compression is only used to make images look worse in image processing.

How does a low-pass filter work in image filtering?

• A low-pass filter enhances high-frequency components while reducing low-frequency components.

• A low-pass filter completely removes all frequencies from the image.

• A low-pass filter distorts the image by amplifying all frequencies equally.

• A low-pass filter allows low-frequency components to pass through while attenuating high-frequency components.

What are the common algorithms used for edge detection?

• Laplacian

• Gaussian

• Sobel, Prewitt, Canny, Roberts Cross

• Frei-Chen

• Kirsch

Discuss the different methods of image segmentation.

• Smoothing, classification, template matching

• Thresholding, clustering, edge detection, region growing, watershed segmentation

• Morphological operations, feature extraction, template matching

• Histogram analysis, template matching, noise reduction

Explain the role of histograms in color correction.

• Histograms help in identifying color balance issues and tonal range distribution in an image, aiding in making precise color corrections.

• Histograms are used for adjusting image resolution, not color correction.

• Histograms provide information on image file size, not color balance.

• Histograms are only relevant for black and white images, not color correction.