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Digital Image Processing
MS – Computer ScienceManipal University
Previous Year Question Papers (Unit Wise)
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Introduction 1/3
Color representation and color models
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Introduction 2/3
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Introduction 3/3
Definition of 2D fourier transform and how it is used in image processing
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Image Operations 1/2
Describe the method of spatial filtering? Describe the different masks used for edge detection and the theory behind them.
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Image Operations 2/2
Describe the frequency domain filters Ideal LPF, Butterworth LPF and Gaussian LPF used in Image Processing. How are they useful in image processing.
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Image Analysis 1/2
What is point processing? Describe contrast stretching, log transformation and Power law transformation with neat diagrams for all the different transformations
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Image Analysis 2/2
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Image Segmentation
What is image segmentation? How is it useful? Describe adaptive thresholding, region splitting and region merging method of segmentation.
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Image Data Compression 1/3
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Image Data Compression 2/3
Compression of images-Huffman and Arithmetic coding
MPEG II and MPEG 4. - http://www.buzzle.com/articles/mpeg2-vs-mpeg4.html
What is meant by GOP? Explain the need for I P and B frames in MPEG2
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Image Data Compression 3/34.Define the wavelet transform for any function(). What is thecharacteristics of wavelet5.Explain the concept of dilation and translation in wavelet transform.
http://davis.wpi.edu/~matt/courses/wavelets/
.What is multi resolution analysis and how it is used in image processing. - http://www.multiresolution.com/cupbook.pdf
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NOT ATTEMPTED
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EXTRA SLIDES
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M. Wu: ENEE631 Digital Image Processing (Spring'09)
Lec1 – Introduction [16]
Sampling and Quantization• Computer handles “discrete” data.• Sampling
– Sample the value of the image at the nodes of a regular grid on the image plane.
– A pixel (picture element) at (i, j) is the image intensity value at grid point indexed by the integer coordinate (i, j).
• Quantization– Is a process of transforming a real valued sampled
image to one taking only a finite number of distinct values.
– Each sampled value in a 256-level grayscale image is represented by 8 bits.
=> Stay tuned for the theories on these in future weeks. 0 (black)
255 (white)
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"simultaneous contrast" digital image processing
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17
Sampling, Quantization, and Operations
• m-adjacency
Relationships between pixels
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DCT versus DFT•DCT has a higher compression efficiency than DFT does
•DCT avoids the generation of spurious spectral components
DFT periodicity DCT periodicity
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DCT vs. DFT