IMAGE PROCESSINGBy-

M.SriHariV.Ashwin

Introduction Ultimate aim Acquiring images-real time example Types Color spaces Real time processing Compression Huffman coding Conclusion bibliography

Contents

Processing or altering the existing image in the desired manner.

It pertains to the analysis of the pictorial representation.

The main instance of image processing is Human Eye that receives , enhances and store images at enormous rate.

Image processing-An introduction

Extract important features from image data By doing so, a description, understanding

and interpretation can be provided by the machines.

There are applications to extract information

But there is no proper tool to analyze.

Ultimate Aim

Scientific instruments commonly produce images to the operator rather than communicating through audible tone.

Space missions always have cameras . The success of the mission can be

measured by the quality of the images.

Acquiring images..

Mars Exploration Rover(MER) began in 2003 by sending 2 rovers MER-A and MER-B

The image of the planet Earth from Mars is given in the next slide.

Real time example-space

Planet Earth from Mars

The image of the planet Earth was taken by Rover during its 529th day on the martian surface.

The image is compressed and then sent to the operator for efficiency.

So this is where image processing is used.

Planet Earth from Mars

Image-to-image transformation. Image-to-information transformation. Information-to-image transformation.

Types of image processing

Conversion from RGB to YIQ/YUV loses no information.

Y, the “luminance” signal, is just the brightness of a panchromatic monochrome image displayed in black and white TV

Color spaces

Real time image processing

An interactive image processing followed in many countries

Redundant information can be compressed. Identical information can be grouped. Without any change in picture quality.

Lossless image compression

Run length Encoding grouping up of redundant information and compressing it.

Image compression-TIFF

Compression by huffman coding. Loss in image quality. This is the first image on the internet.

Lossy image compression

Split images into color and gray scale information.

Group pixel into 8x8 blocks and transform through discrete cosine transform.

Image compression-JPG

Proposed by Dr. David A. Huffman in 1952◦ “A Method for the Construction of Minimum

Redundancy Codes” Huffman coding is a form of statistical

coding Not all characters occur with the same

frequency. But allocated the same size. 1 char = 1 byte

Huffman coding

Scan text to be compressed and tally the occurrences of all characters.

Sort or prioritize characters based on number of occurrences in text.

Build Huffman code tree based on prioritized list.

Perform a traversal of tree to determine all code words.

Scan text again and create new file using the Huffman codes.

Huffman algorithm

Char CodeE 0000i 0001y 0010l 0011k 0100. 0101space 011e 10r 1100s 1101n 1110a 1111

Encoding a file

Eerie eyes seen near lake. 00001011000001100111000101011011010

01111101011111100011001111110100100101

Once the receiver receives the encoded characters , it decrypts with the help of tree.

0-move left 1-move right

Encoding example

Image processing is any form of signal processing.

Input is an image. Output may be information or image.

To conclude

Lossy compression by Dr.Zhu liu. John C. Ross. Image Processing Hand book,

CRC Press. 1994 Cs102 huffman coding.

Bibliography

Thank you