{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

6 - OnlineLecture6 LearningObjectives DataCompression...

This preview shows pages 1–7. Sign up to view the full content.

Mulitimedia Computing Online Lecture-6 Learning Objectives: Data Compression Text Compression Huffman Coding  LZW Coding Arithmetic Coding Image Compression GIF JPEG Standard JPEG 2000 Solution to Some Problems Some Recommended  Problems Instructor-in-Charge Dr. Mukesh Kumar  Rohil WILPD, BITS, Pilani Rajasthan Monday, March 15, 2010 1 WILPD, B.I.T.S., PILANI EA ZC473 Multimedia Computing On-Line Lecture-6

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Data Compression Why data  compression? Why we are able to  compress? Lossless compression Lossy compression Source Coding Entropy Coding Hybrid Coding Run-Length Coding Huffman Coding LZW Coding Arithmetic coding Image Compression JPEG (details) JPEG 2000  (Overview) * Video  Compression Monday, March 15, 2010 2 WILPD, B.I.T.S., PILANI EA ZC473 Multimedia Computing On-Line Lecture-6
3 Q1.   Find Huffman codes and compression ratio (C.R.) for Table 1,  assuming that uncompressed representation takes 8-bit per character  and assume that size of Huffman table is not part of the compressed  size. Table 1: Char A B C D E F G H Freq 90 60 50 20 12 8 7 3 Huffman Codes: A B C D E F G H 00 01 10 111 1101 11001 110000 110001 11 10 01 000 0010 00110 001111 001110 Monday, March 15, 2010 WILPD, B.I.T.S., PILANI EA ZC473 Multimedia Computing On-Line Lecture-6

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Huffman Coding - Example Huffman Tree         250      /         \              150      100            /    \      /     \  A    B   C     50                    /     \                 30      D               /    \           18      E            /   \       10      F        /   \     G     H  Monday, March 15, 2010 WILPD, B.I.T.S., PILANI EA ZC473 Multimedia Computing On-Line Lecture-6 4 Char A B C D E F G H Freq 90 60 50 20 12 8 7 3 Huff- man Code 00 01 10 111 1101 11001 110000 110001 C.R. = (250*8) / (2*90 + 2*60 + 2*50 + 3*20 + 4*12 + 5*8 + 6*7 + 6*3) = 3.29
5 Q2.  Find Huffman code-words and the achieved compression ratio  using Huffman  coding, for the data given in Table 2. Assume  originally a character is stored using 8-bit. Table 2: Code: 00 01 11 1000 1001 10100 10101 10110 10111 Char C E T B V S U N R Freq 130 120 58 30 22 10 9 8 5 C.R. = (392*8) / (2*130 + 2*120 + 2*58 + 4*30 + 4*22 + 5*10 + 5*9 + 5*8 + 5*5) = 3.187 Monday, March 15, 2010 WILPD, B.I.T.S., PILANI EA ZC473 Multimedia Computing On-Line Lecture-6

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Decompression - Huffman  Codes Compress DEAF using above Huffman  Codes. 111 1101 00 11001
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

Page1 / 31

6 - OnlineLecture6 LearningObjectives DataCompression...

This preview shows document pages 1 - 7. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online