Lossless Image compression Based on Discrete wavelet Transform

ABSTRACT

A fundamental goal of digital image compression is to reduce the bit rate for transmission or data storage while maintaining an acceptable fidelity or image quality. In this study a proposed coding (compression) scheme for grey scale image by discrete wavelet transform (DWT). This method is utilized to take the advantages provided by all of them to get high compression ratio with acceptable recovered image quality. First, the discrete wavelet transform is performed on the original image using bi-orthogonal filter (bior5.5) resulting in number of sub-bands according to the decomposition level that can be one in the proposed scheme. This proposed system is implemented using MATLAB platform. Lossless Image compression Based on Discrete wavelet Transform

INTRODUCTION

The Data compression is the technique to reduce the redundancies in data representation in order to decrease data storage requirements and hence communication costs. Reducing the storage requirement is equivalent to increasing the capacity of the storage medium and hence communication bandwidth. Thus, the development of efficient compression techniques will continue to be a design challenge for future communication systems and advanced multimedia Application.

Still image coding is an important application of data compression. When an analog image or picture is digitized, each pixel is represented by a fixed number of bits, which correspond to a certain number of gray levels. In this uncompressed format, the digitized image requires a large number of bits to be stored or transmitted. As a result, compression becomes necessary due to the limited communication bandwidth or storage size.

Existing System

1.Image compression has been implemented by DCT.

2.DCT need number of iterations to compress an gray scale image.

3.Latency is more in this system

Proposed System

1.Image compression has been implemented by DWT.

2.DWT works on whole image by folding an image to the maximum level to compress an gray scale image.

3.DWT has less time complexity than other techniques.

 

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