ECE3005
Pre-requisite
Digital Image Processing
ECE2006 - Digital Signal Processing
L T P J C
3 0 2 0 4
Syllabus version
1.1
Course Objectives:
1. To give the fundamentals of digital image processing and to introduce the concepts of two
dimensional transformation techniques on spatial images.
2. To apply various filtering methods for image enhancement.
3. To understand the concepts of color image processing and different image compression
techniques.
4. To study various image segmentation algorithms and to introduce the concept of descriptors
for boundary representation of images.
Course Outcomes:
1. Perform histogram processing and apply spatial filter on images.
2. Apply transformation techniques like 2D-FFT, DWT and KL transform on images.
3. Perform filtering in frequency domain for image enhancement.
4. Process the color image in three dimensions for enhancement.
5. Design various standard image compression techniques and see their effects in terms of data
reduction.
6. Apply various image segmentation algorithms and also, represent the same using boundary
and region descriptors
7. Design and implement algorithms using the imbibed image processing concepts
Student Learning Outcomes (SLO): 1,2,14
Module:1 Basics of Digital Image Processing
6 hours
Introduction, Fundamental steps in DIP – Elements of visual perception -Image sensing and
Acquisition – Image Sampling and Quantization – Imaging geometry, discrete image mathematical
characterization- Basic relationship between pixels. Basic Gray level Transformations – Histogram
Processing – Smoothing spatial filters- Sharpening spatial filters.
Module:2 Image Transforms
8 hours
Two dimensional Fourier Transform- Properties – Fast Fourier Transform – Inverse FFT- Discrete
cosine transform and KL transform-Discrete Short time Fourier Transform. Discrete Wavelet
Transform- the Haar wavelet family – Multiresolution analysis: shifting and the scaling functionsImplementation using filters.
Module:3 Image Enhancement in Frequency domain
6 hours
Smoothing frequency domain filters- Sharpening frequency domain filters- Homomorphic filtering,
Restoration filters
Module:4 Color Image Processing
Color models-Pseudo color image processing- Color transformations
5 hours
Module:5
6 hours
Image Compression
Overview of Image Compression Techniques- Quantization- Entropy Encoding-JPEG and MPEG
standards
Module:6 Image Segmentation
7 hours
Detection of discontinuities – Edge linking and boundary detection- Thresholding -Edge based
segmentation-Region based segmentation- Matching-Morphological segmentation- Watershed
algorithm
Module:7 Representation and Description
5 hours
Boundary descriptions-Region descriptors- Use of Principal Components and Description, Texture
description.
Module:8
Contemporary issues
2 hours
Total lecture hours:
45 hours
Text Book(s)
1. Anil K. Jain, “Fundamentals of Digital Image Processing”, 2015, 1 st edition, Pearson India,
India
2. Rafael C. Gonzalez & Richard E. Woods, “Digital Image Processing”, 2017, 4 th edition,
Pearson Education, USA
Reference Books
1. Mark Nixon & Alberto Aguado, “Feature Extraction, and Image Processing”, 2012, 3 rd edition,
Elsevier’s Science & Technology Publications, Woborn MA, Great Britain.
2. Scott E. Umbaugh, “Digital Image Processing and Analysis: Human and Computer Vision
Applications with CVIP tools”, 2011, 2 nd edition, CRC press, Boca Raton, FL, USA.
Mode of Evaluation:Internal Assessment (CAT, Quizzes, Digital Assignments) & Final
Assessment Test (FAT)
List of Challenging Experiments (Indicative)
1 Perform point to point operation on the given image and compute the
following and interpret changes in image
• Image Negative
• Power law transformation
• Log transform
2 Perform histogram equalization for the given image and analyze the
enhanced quality of the image.
• Read the input Image of size 256 × 256 and perform up sampling
and down sampling by a factor of 2. Show the effect of image
shrinking and zooming.
• Read the input image of size 256 × 256 and show the effect of gray
level variation for L = 32, 4, 2.
• Perform contrast stretching for the given poor contrast image.
3 Extract all 8-bit planes from given image and comment on the number of
visually significant bits in each image.
2 hours
2 hours
1 hour
4
To detect moving objects in an image sequence using background
subtraction algorithm.
5 For the given 512×512 image (lena.jpg), implement the following spatial
domain filtering techniques
• Low Pass Filtering
• High Pass Filtering
• Order Statistics (Median) Filtering
6 To perform DFT for the given image and obtain its Fourier spectrum.
Verify the symmetric property of DFT and compare the result with
Discrete Cosine Transform.
7 Removal of fine details in an image by frequency domain processing and
analysis of information loss.
8 Identifying objects in an image based on their boundaries
9 Compute the Fourier Transform of the given images and add them using
blend. Take the inverse Fourier Transform of the sum. Explain the result.
10 Perform logical operations on the given images.
11 Perform image enhancement, feature extraction studies and compression
using DFT.
12 Perform image enhancement, feature extraction studies and compression
using DCT.
13 Perform image enhancement, feature extraction studies and compression
using DWT.
Total laboratory hours
Mode of evaluation:Continuous Assessment & Final Assessment Test (FAT)
Recommended by Board of Studies
28-02-2016
Approved by Academic Council
No. 47
Date
05-10-2017
2 hours
2 hours
2 hours
2 hours
1 hour
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2 hours
4 hours
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4 hours
30 hours