07-02-2013, 03:57 PM
Wavelet-based Image Compression
Wavelet-based Image Compression.ppt (Size: 3.71 MB / Downloads: 197)
Abstract
Wavelet based image compression has been a focus of research in recent days.we propose a compression technique based on modification of original EZW coding.
In this lossy technique, we try to discard less significant information in the image data in order to achieve further compression with minimal effect on output image quality.
The algorithm calculates weight of each subband and finds the subband with minimum weight in every level.
Introduction
During the past years, there has been tremendous increase in user demand for multimedia content.
Multimedia content takes up a lot of storage space and bandwidth:
A truecolor 512x512 image would take 0.75 Mbyte of space.
One second of NTSC colour video takes about 23 Mbytes ! [1]
Hence, we need to compress images and video.
What is wavelet compression?
Wavelet is a transform just like Fourier, DCT, Laplace, etc...
It is the newest compression technology available on consumer market [2].
It performs better than existing techniques in this area: it achieves better quality and higher compression ratios.
It has many applications in digital signal processing.
Compressing still images
Image compression techniques operate by removing redundancy and details not perceived by the human eye .
Compression is achieved by keeping only the most significant wavelet coefficients (lossy compression).
Compression algorithm allows progressive transmission: most important information transmitted first.
Compressing video
Compression takes advantage of inter-frame redundancy: successive frames have very little differences.
Video compression and transmission over heterogeneous networks requires:
Scalability.
Packet loss and error resilience.
Low delay in real-time situation.
Low Jitter.