vanmathy v DIP.pptx

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There are basic types of redundancy five types, coding redundancy, inter pixel redundancy,psycho visual redundancy,chromatic redundancy,lossless compression algorithms

Technology

TOPIC
DIGITAL IMAGE PROCESSING
CODING REDUNDANCY
INTER PIXEL REDUNDANCY
 PSYCHO VISUAL REDUNDANCY
CHROMATIC REDUNDANCY
 LOSSLESS COMPRESSION ALGORITHMS

Chromatic Redundancy
• Chromatic redundancy refers to the
unnecessary colors in an image.
• Colors that are not perceived by
human visual system can be
removed without effecting quality of
image.
• Difference b/w original &
reconstructed image is called
distortion.
• The image quality can be assed
based on the subjective picture
quality scale(PQS).

• Lossless compression is generally
used for text compression: data such
as database records, spreadsheets,
and word processing files.
• When encoding and recovering this
type of data, it is crucial to preserve
each character exactly, because very
small differences can have huge
impact.
• For example, a tiny difference in a text
can create very different meaning:

Lossless Compression
Algorithm
• Run-Length Coding
• Huffman Coding
• Shannon-Fano Coding
• Arithmetic Coding

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vanmathy v DIP.pptx

1. NADAR SARASWATHI COLLEGE OF ARTS&SCIENCE,THENI DEPARTMENT OF COMPUTER SCIENCE&INFORMATION TECHNOLOGY V.VANMATHY II-MSC(CS)

2. TOPIC DIGITAL IMAGE PROCESSING CODING REDUNDANCY INTER PIXEL REDUNDANCY  PSYCHO VISUAL REDUNDANCY CHROMATIC REDUNDANCY  LOSSLESS COMPRESSION ALGORITHMS

3. Coding Redundancy

7. Inter pixel Redundancy

10. Psycho Visual Redundancy

11.

12. Chromatic Redundancy

13. Chromatic Redundancy • Chromatic redundancy refers to the unnecessary colors in an image. • Colors that are not perceived by human visual system can be removed without effecting quality of image. • Difference b/w original & reconstructed image is called distortion. • The image quality can be assed based on the subjective picture quality scale(PQS).

14. Lossless compression algorithm

15. • Lossless compression is generally used for text compression: data such as database records, spreadsheets, and word processing files. • When encoding and recovering this type of data, it is crucial to preserve each character exactly, because very small differences can have huge impact. • For example, a tiny difference in a text can create very different meaning:

16.

17.

18. Lossless Compression Algorithm • Run-Length Coding • Huffman Coding • Shannon-Fano Coding • Arithmetic Coding

vanmathy v DIP.pptx

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