EE211A
Homework #5, 11/30/2015, Due: 12/06/2015
Please type your results or scan the written results.
1. Consider a video of resolution 320240 and 15 frames per second. Assume that youre trying to encode it
using MPEG-1. Supposing it is that of an airplan
EE211A Digital Image Processing I
November, 9 2015
Introduction to Wavelets
Prof. Ofer Hadar
Communication Systems Engineering Dept., BGU
URL: http:/www.cse.bgu.ac.il/~hadar
This lecture is based on material of Professor Ramin Zabih
CORNELL UNIVERSITY
EE2
Discrete Cosine Transform (DCT)
video codec
future: some changes block size
integer dct no too many differences
EE211A - Digital image processing I
November 9, 2015
EE211A, Prof. Ofer Hadar, DCT , Week 7, 11.9.2015
An Example of 1D Transform
with Two Vari
ZeroTree Coding
EZW: Embedded ZeroTree Wavelet
Encoding
Nimrod Peleg
Update: Dec. 2000
What is Embedded ?
Progressive: every bit you add - you increase
the accuracy of the number you transfer - as
in:
You can stop at any accuracy you like !
Nowwe need
Some applications of wavelets
Anna Rapoport
FBI Fingerprint Compression
Between 1924 and today, the US Federal Bureau of
Investigation has collected over 200 million cards of
fingerprints
Some come from employment and security checks, but
114.5 million c
Exercise
Assume a multimedia transmission thought channel communication which is
limited to1.5 Mbps. The video file is transmitted with an Audio file, the Audio has
an average bit-rate of 300 Kbps.
The digital video is with format PAL and compressed as MP
MULTIMEDIA COMPRESSION
2012/2013 ,"
MPEG STANDARDS
Dr. Dan Grois
Communication Systems Engineering Department
Ben-Gurion University of the Negev
This material is based on lecture notes of John G. Apostolopoulos, Streaming Media System
Group, HP Labs, Pa
Zonal coding
keep
Information theory says coefficients
with maximum variance carry the
most information.
15 out of 64 transform coefficients
, with largest variance, are kept
discard
2001 Bijan Mobasseri
76
Quantization
Retained coefficients are quantize
Introduction to Video Compression
10/21/2015
Part B
EE211A Digital Image Processing I
Part of the slides here are taken from the course:
EE 465 Introduction to Digital Image Processing
Prof. Ofer Hadar
Communication Systems Engineering Dept., BGU
URL: htt
Data Compression: Advanced Topics
Huffman Coding Algorithm
Motivation
Procedure
Examples
EE465: Introduction to Digital Image Processing
1
Recall: Variable Length Codes (VLC)
Recall:
Self-information
I ( p) log 2 p
It follows from the above formula th
Binary Image Compression
The art of modeling image source
Image pixels are NOT independent events
Run length coding of binary and graphic
images
Applications: BMP, TIF/TIFF
Lempel-Ziv coding*
How does the idea of building a dictionary can
achieve da
10/16/2015
EE211A
Homework 2
Image Restoration
Due date: 10/26/2015
Introduction
Images are often degraded during the data acquisition process. Degradation comes in many forms
such as motion blur, noise, and camera misfocus. The purpose of image restorati
10/23/2015
EE211A
Homework 1 Solution
MATLAB (Processing of Color Images) & Resolution
Exercise 1 (Color Image Creation)
Correction:
r = [1,0,0;1,0,1;1,0,1];
(a) The Matlab code that generates the rgb components for and displays the requested color image
The H.264 Standard
Nov. 30, Dec. 2, 2015
E211A Digital Image Processing I
Prof. Ofer Hadar
Communication Systems Engineering Department
Ben-Gurion University of the Negev
URL: http:/www.cse.bgu.ac.il/~hadar
Copyright @1999, O. Hadar
EE211A, Week 10, The H
EE5585 Data Compression
March 14, 2013
Lecture 15
Instructor: Arya Mazumdar
Scribe: Khem Chapagain
Scalar Quantization Recap
Quantization is one of the simplest and most general ideas in lossy compression. In many lossy
compression applications, we are re
EE211A
Homework #4, 11/19/2015, Due: 11/27/2015
NOTE: Please hand in the results and the codes.
1. DCT Representation of Images and Quantization of DCT coefficients
This problem is intent to give you a quick start on DCT transform and quantization, which
EE211A Homework 3
Name: Shubham Agarwal
UCLA-ID: 204587029
1. Binary variable entropy and Huffman coding
A scanner scans each page in a raster-scan order (from the top-left to the bottom-right)
and represents the line art pixels by only one binary bit wit
JPEG
November , 30, 2015
E211A Digital Image Processing I
1
EE211A, Prof. Ofer Hadar, Week 10
:The JPEG standard.
JPEG : Background
JPEG Joint Photographic Expert Group Joint
standards committee of ITU-T and ISO
Flexible standard for monochrome and colo
Motion Estimation for compression
November , 25, 2015
E211A Digital Image Processing I
Prof. Ofer Hadar
Communication Systems Engineering Department
Ben-Gurion University of the Negev
URL: http:/www.cse.bgu.ac.il/~hadar
Based on: 1 Lecture of Osnat Bar Ni
Motion Estimation
Yao Wang
Polytechnic School of Engineering, New York University
Yao Wang, 2015
EL-GY 6123: Image and Video Processing
1
Outline
3D motion model
2-D motion model
2-D motion vs. optical flow
Optical flow equation and ambiguity in motion e
EE211A Digital Image Processing I
30 November 2015
MPEG-4
Prof. Ofer Hadar
Communication Systems Engineering Dept., BGU
URL: http:/www.cse.bgu.ac.il/~hadar
This material was written by Professor Magda El. Zarki
University of California, Irvine, CA
E-mail:
Image Compression using
Vector Quantization
Nopparat Pantsaena
Manas Sangworasil
Chinnapat Nantajiwakornchai
Tanasak Phanprasit
Research Center for Communication and Information
Technology (ReCCIT)
King Mongkuts Institute of Technology Ladkrabang (KMITL)
EE211A
Digital Image Processing I
November 23, 2015
Week 9
Scalar Quantization Mathematical Model
EE211A - Prof. Ofer
Hadar, Week 9 :
Scalar Quantization Mathematical Model
Definition of Quantization
Definition:
Quantization: a process of representing a l
Outline of Vector Quantization of
Images
S.R.Subramanya
1
VQ Coding Outline
Divide data (signal) into non-overlapping vectors
(Each vector contains n elements (pixels/samples)
For each image vector :
Find closest vector in codebook
Get its index in c
Lecture 7
Scalar quantization part II
ESS155 Data Compression 2004
Overview
Pdf-optimized quantization
The quantizer is optimized to match the pdf of
the source
Companded quantization
A simplified version of pdf-optimized
quantization
Entropy-coded q