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Course Content
MODULE 1
0/8
INTRODUCTION
04:42
1. What is digital image? Explain the fundamental steps of digital image processing
08:04
2. Discuss the application of image processing in any 5 fields.
06:49
3. Explain with neat diagram, image acquisition using a sensor strips
07:27
4. Explain the 4, 8 and m connectivity of pixels with the help of an example
03:45
5.An image shown below
06:41
6. What are the elements of visual perception in image processing?
03:12
7.What are the elements of visual perception in image processing
07:09
MODULE 2
0/7
1. Illustrations of Grayscale/Intensity Transformation Functions with neat diagram: a) Piece-wise Linear Transformation b) Grey level slicing
05:53
2. Explain the following concepts with proper examples: (i) Histogram Processing (ii) Histogram Equalization (iii) Histogram Matching/ Specification
06:07
3. Illustrate the representation of Digital Images with necessary diagrams and Matrices
02:58
4. Obtain the equation for 2D Discrete Fourier transform and its inverse from the continuous transform of sampled function of one variable
03:11
5. Explain the fundamentals of Filtering in Frequency domain
02:56
6. Demonstrate the model of Image Degradation/ Restoration Process
02:37
7. Explain: (i) Gaussian Low Pass Filter (ii) Gaussian High Pass Filter
03:33
MODULE 3
0/5
1. EXPLAIN THE BASIC INTENSITY TRANSFORMATION FUNCTIONS/ POINT PROCESSING TECHNIQUES
03:07
2. EXPLAIN SPECIAL FILTERING WITH EXAMPLE
02:53
3. EXPLAIN SMOOTHING SPATIAL FILTERS /AVERAGING FILTERS WITH NEAT DIAGRAM
01:50
4. EXPLAIN SHARPENING SPATIAL FILTERS WITH GRADIENT AND LAPLACIAN OPERATORS.
03:07
5.EXPLAIN A. UNSHARP MASKING B. HIGHBOOST FILTERING
03:02
MODULE 4
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1. EXPLAIN THE CONCEPT OF FREQUENCY DOMAIN FILTERING
02:49
2. EXPLAIN IMAGE SMOOTHING USING FREQUENCY DOMAIN FILTERS
04:46
3. DEFINE CHROMATICITY THAT DISTINGUISH ONE COLOUR FROM ANOTHER.
04:23
4. DESCRIBE RGB COLOUR MODEL WITH NECESSARY DIAGRAM AND EQUATIONS.
02:30
5. DESCRIBE CMY AND CMYK COLOUR MODEL WITH NECESSARY DIAGRAM AND EQUATIONS.
01:37
6. DESCRIBE HSI COLOR MODEL WITH NECESSARY DIAGRAM.
02:16
7. DESCRIBE COLOR IMAGE PROCESSING WITH DIAGRAM.
02:35
MODULE 5
0/7
1.With necessary equations and graph, explain any four noise probability density functions.
03:52
2. Explain minimum mean square error filtering method of restoring images.
02:08
3.Explain inverse filter and Weiner filter with the help of equations. Explain the advantages of Wiener filter over inverse filter.
01:49
4. Define the process of image restoration. How is restoration is different from enhancement?
03:49
5. With necessary mathematical equations, explain estimate the degradation function by modeling.
02:14
6. What are adaptive filters ? Explain adaptive mean filter and its advantages
02:25
7. Explain how image degradation is estimated using, (i) Observation (ii) Experimentation
02:11
DIGITAL IMAGE PROCESSING || ECE stream || Very Important Questions Explained with Concepts || All 5 modules || BEC613C || Last moment exam preparation
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