Exploring Digital Image Processing

What are the primary methods of image acquisition?

• Image editing software

• Film development

• Graphic design techniques

• Digital photography, scanning, MRI, CT, ultrasound

Describe the role of sensors in image acquisition.

• Sensors are used to store images in digital format.

• Sensors convert light into electrical signals to capture images.

• Sensors primarily focus on color correction during image processing.

• Sensors enhance image resolution by adjusting brightness levels.

What is the difference between analog and digital image acquisition?

• Analog images are continuous signals; digital images are discrete pixel values.

• Digital images can be continuously adjusted; analog images cannot.

• Analog images are stored as binary data; digital images are stored as continuous signals.

• Analog images are made of pixels; digital images are made of film.

Explain the concept of sampling in image acquisition.

• Sampling involves the compression of image files to reduce size.

• Sampling is the process of converting a continuous image signal into a discrete signal by measuring light intensity at specific intervals.

• Sampling is the process of enhancing image quality by increasing resolution.

• Sampling refers to the method of applying filters to smooth out images.

What is quantization in the context of image acquisition?

• Quantization refers to the compression of image files.

• Quantization is the method of applying filters to images.

• Quantization is the process of enhancing image resolution.

• Quantization is the process of converting continuous color/intensity values in an image to discrete values.

List and describe two common image enhancement techniques.

• Brightness Adjustment: Changes the overall lightness of an image.

• Image Resizing: Alters the dimensions of the image without enhancing quality.

• 1. Histogram Equalization: Improves contrast by redistributing intensity values. 2. Contrast Stretching: Expands the range of intensity values for a more vibrant image.

• Color Filtering: Applies a color overlay to the image.

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

• Histogram equalization reduces image size by compressing pixel data.

• Histogram equalization changes the color palette of an image to grayscale.

• Histogram equalization blurs images to create a smoother appearance.

• Histogram equalization enhances image contrast by redistributing pixel intensity values to cover the full range, making details more visible.

Explain the purpose of contrast stretching in image enhancement.

• To reduce the size of the image file.

• To convert the image to grayscale.

• To apply a blur effect to the image.

• The purpose of contrast stretching is to enhance the contrast of an image by expanding the range of intensity values.

What are the advantages of using spatial domain methods for image enhancement?

• Advantages of spatial domain methods include simplicity, real-time processing, and effective enhancement of contrast, brightness, and sharpness.

• Requires extensive user input

• High computational cost

• Limited to grayscale images

Define the term 'image filtering' in digital image processing.

• Image filtering is the method of creating a 3D model from a 2D image.

• Image filtering is the process of modifying or enhancing an image by applying a filter to alter pixel values.

• Image filtering refers to the technique of removing all colors from an image.

• Image filtering is the process of compressing an image to reduce its file size.