Digital Image Processing

MS – Computer ScienceManipal University

Previous Year Question Papers (Unit Wise)

Introduction 1/3

Color representation and color models

Introduction 2/3

Introduction 3/3

Definition of 2D fourier transform and how it is used in image processing

Image Operations 1/2

Describe the method of spatial filtering? Describe the different masks used for edge detection and the theory behind them.

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.

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

Image Analysis 2/2

Image Segmentation

What is image segmentation? How is it useful? Describe adaptive thresholding, region splitting and region merging method of segmentation.

Image Data Compression 1/3

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

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

NOT ATTEMPTED

EXTRA SLIDES

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.

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"simultaneous contrast" digital image processing

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Sampling, Quantization, and Operations

• m-adjacency

Relationships between pixels

DCT versus DFT•DCT has a higher compression efficiency than DFT does

•DCT avoids the generation of spurious spectral components

DFT periodicity DCT periodicity

DCT vs. DFT