SECTION – A
Explain the following (Short Answer Type)
Mean Square Error Restoration is a method used in digital image processing to improve image quality by minimizing the difference between the original image and the restored image. It calculates the average squared difference between pixel values and tries to reduce errors during restoration.
Dilation is a morphological operation that increases the size of objects in an image. It adds pixels to the boundaries of objects, making them thicker and more visible.
Mathematical Morphology is a technique used in image processing that focuses on analyzing the shape and structure of objects within an image. It uses operations like dilation and erosion to modify image features.
Opening operation is a combination of erosion followed by dilation. It is mainly used to remove small objects or noise from an image while keeping the main structure intact.
Closing operation is the opposite of opening. It involves dilation followed by erosion and is used to fill small holes and gaps inside objects.
Thinning is a process used to reduce objects in an image to a skeleton-like structure without changing their connectivity.
Thickening is the opposite of thinning. It adds pixels to object boundaries to increase their thickness.
Erosion is a morphological operation that removes pixels from the boundaries of objects, making them thinner.
Degradation functions describe how an image becomes distorted due to noise, blur, or other factors during acquisition or transmission.
Structuring elements are small patterns or shapes used in morphological operations to process images.
Questions (Section A):
What is Mean Square Error Restoration?
Define Dilation in image processing.
What is Mathematical Morphology?
What are Opening and Closing operations?
What is the difference between thinning and thickening?
SECTION – B
Attempt any five (Long Answer Type)
A Band-Pass Filter is used in image processing to allow a specific range of frequencies to pass while blocking lower and higher frequencies. It is commonly used to enhance certain details in images.
The degradation model explains how an image becomes distorted due to noise or blur. It shows the relationship between the original image, degradation function, and noise. Restoration techniques aim to recover the original image from the degraded version.
Histogram computation is a method used to analyze the distribution of pixel intensity values in an image. It helps in understanding image brightness and contrast. The cumulative histogram shows the total number of pixels up to a certain intensity level.
Edge detection is the process of identifying boundaries of objects within an image. Line detection identifies specific linear patterns such as roads, text lines, or edges.
Noise models describe unwanted variations in images caused by electronic interference or environmental factors. Common noise types include Gaussian noise and salt-and-pepper noise.
Smoothing filters like mean, median, minimum, and maximum filters are used to reduce noise and improve image quality. Weighted filters give different importance to neighboring pixels during smoothing.
Questions (Section B):
What is a Band-Pass Filter?
Explain the degradation model in image processing.
What is histogram and cumulative histogram?
Define edge detection and line detection.
Explain different types of noise in images.
SECTION – C
Attempt any two (Descriptive Type)
Hit-Miss Transform is a morphological operation used to detect specific shapes or patterns in binary images. It helps identify object structures by comparing them with predefined patterns.
Periodic Noise Reduction is a technique used to remove repeating patterns of noise using frequency domain filtering methods. It improves image clarity by eliminating unwanted frequency components.
Arithmetic and logical operations in image processing include addition, subtraction, AND, OR, and NOT operations. These are used to combine images, enhance features, and perform masking operations.
Questions (Section C):
What is Hit-Miss Transform and why is it used?
Explain periodic noise reduction in frequency domain.
What are arithmetic and logical operations in image processing?
