WAVELET VIDEO PROCESSING

by

N.SUDHEER KUMAR 07121A0464

Under the guidance of

Mr.D.DAMODARAM ,M.Tech Associate Processor

Department of Electronics and Communication Engineering

SREE VIDYANIKETHAN ENGINEERING COLLEGE

Sri Sainath Nagar, A.Rangampet, Tirupathi-517102

A Seminar on

BATCH CODE:1105

OUTLINE Objective Introduction Image Compression Lossy And Lossless Compression Bit Allocation Classifying of Image Data Quantization and Entropy EncoderChip Provides Wavelet TransformAdvantages Applications References

OBJECTIVEWavelet video processing technology offers some alluring

features, including high compression ratio and eye pleasing enlargements. one of the hottest area of advanced form of compression is wavelet compression.

INTRODUCTIONThe biggest obstacle to the multimedia revolution is digital

obesity. This is the blot that occurs when pictures,sounds and vedio are converted from their natural analog form into computer language for manipulation or trasmission.

In the present explosion of high quality data,te need to compress it with less distortion of data is the need of the hour.

Compression lower the cost of storage and transmission by packing data into a smaller space.

IMAGE COMPRESSION•Image compression is a technique for processing images. It is the compressor of graphics for storage or transmission. Compressing an image is significantly different than compressing saw binary data .

•Some general purpose compression programs can be used to compress images, but the result is less than optimal .

Compression is basically of two types.1. Lossy Compression2. Lossless Compression.

LOSSY COMPRESSION

•Lossy compression of data concedes a certain loss of accuracy in exchange for greatly increased compression. An image reconstructed following lossy compression contains degradation relative to the original. Often this is because the compression scheme completely discards redundant information.

LOSSLESS COMPRESSION

•Lossless compression consists of those techniques guaranteed to generate an exact duplicate of the input data stream after a compress or expand cycle. Here the reconstructed image after compression is numerically identical to the original image

•This is the type of . compression used when storing data base records, spread sheets or word processing files

LOSSY COMPRESSION

Source Quantizer Entropy Encoder

encoder

Input signal/image Compressed signal/ image

To create a representation for the data in which there is less correlation among the coefficient values. This called decorrelating the data.

STEPS IN COMPRESSION

The usual steps involved in compressing an image are

1. Specifying the rate (bits available) and distortion (tolerable error) parameters for the target image.

2.Dividing the image data into various classes, based on their Importance.

3.Dividing the available bit budget among these classes such that the distortion is a minimum.

4.Quantize each class separately using the bit allocation information. Encode each class separately using an entropy coder and write to the file.

BIT ALLOCATION1. Initially, all classes are allocated a predefined maximum numbers of

bits.

2.For each class, one bit is reduced from its quota of allocated bits, and the distortion due to the reduction of that one bit is calculated.

3.Of all the classes, the class with minimum distortion for a reduction of 1 bit is noted, and 1 bit is reduced from its quota of bits.

4.The total distortion for all classes D is calculated.

5.The total rate for all the classes is calculated as R = p (i) * B (i), where p is the probability and B is the bit allocation for each class.

6.Compare the target rate and distortion specifications with the values obtained above. If not optimal, go to step 2.

CLASSIFIENG IMAGE DATA

An image is represented as a two dimensional array of coefficients, each coefficient representing the brightness level in that point.

Most natural images have smooth colour variations, with the fine details being represented as sharp edges in between the smooth variations. Technically, the smooth variations in colour can be termed as low frequency variations and the sharp variations as high frequency variations.

Separating the smooth variations and details of the image can be done in many ways. One such way is the decomposition of the image using Discrete Wavelet Transform (DWT).

FIG: Illustration of DBUTM

Just as a forward transform is used to separate the image data into various classes of importance a reverse transform is used to reassemble the various classes of data into a reconstructed image.

We start from the topmost level, apply the filters coloumn wise first and then row wise and proceed to the next level, till we reach the first level.

QuantizationQuantization refers to the process of approximating

the continuous set of values in the image data with a finite set of values.

The quantizer is a function whose set of output values are discrete, and usually finite.

Entropy codingEntropy means the amount of information present

in the data, and an entropy coder encodes the given set of symbols with the minimum number of bits required to represent them.

CHIP PROVIDES WAVELET TRANSFORMS

Digital video

1/0 post

Wavelet filters,

decimator and

interpolator

Adaptive quantizer

Run length coder

Huffman coder

Host 1/0 post and

FIFOOn chip transform

buffer

Digital Component Video I/O

Host

Analog Devices have developed a family of general purpose wavelet-codec chips. The latest chip, ADV6OLIC, claims to accommodate compression ratios from visually losslessIn wavelet-based compression processing, the silicon area needed for compression is the same as the area needed for decompression. In contrast, other compression techniques require more work and special circuitry to compress than to decompress a signal.  

ADVANTAGES

The high image compression ratios reduces the hard disk storage capacity for real time recording and for archival storage

it has higher resolution than DCT based JPEG and MPEG

The compressed video file cannot be edited

APPLICATIONS

• JPEG2000 uses wavelet transforms to compress images.

• MPEG-4 uses wavelet tiling to allow the division of images into several tiles, each with separate encoding

• Kallix corp. uses wavelet technology in to video surveillance systems.

REFERENCES

1.Bill Travis, “Wavelets both implode and explode images”, EDN, December 2000

2.Raghuveer.M.Rao and Ajit.S.Bopardikar, “Wavelet Transforms,

3.Introduction to theory and applications”, Pearson Education Asia.

4.Jaideva.C.Goswami and Andrew.K.Chan,”Fundamentals of wavelets,theory,algorithms and application”, Wiley Interscience Publication.

5.Chan.Y.T,”Wavelet basics”, Kluwer Academic Publishers.

6.http:/engineering.rowan.edu/~polikar/WAVELETS/WTtutorial.html