Uncompressed multimedia data requires considerable storage capacity and transmission bandwidth. Despite rapid progress in mass storage density processor speeds and digital communication system performance, demand for data storage capacity and data transmission bandwidth continues to outstrip the capabilities of available technologies. The recent growth of data intensive multimedia-based web applications have not only sustained the need for more efficient ways to encode signals and images but have made compression of such signals central to storage and communication technology.
For still image compression, the joint photographic experts group (JPEG) standard has been established. The performance of these codes generally degrades at low bit rates mainly because of the underlying block-based Discrete cosine Transform (DCT) scheme. More recently, the wavelet transform has emerged as a cutting edge technology, within the field of image compression. Wavelet based coding provides substantial improvements in picture quality at higher compression ratios. Over the past few years, a variety of powerful and sophisticated wavelet based schemes for image compression have been developed and implemented. Because of the many advantages, the top contenders in JPEG-2000 standard are all wavelet based compression algorithms.
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. This is because images have certain statistical properties which can be exploited by encoders specifically designed for them. Also some finer details in the image can be sacrificed for saving storage space.
Compression is basically of two types.
1. Lossy Compression
2. Lossless 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. Under normal viewing conditions no visible is loss is perceived. It proves effective when applied to graphics images and digitized voice.
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. Lossless compression can only achieve a modest amount of compression. This is the type of compression used when storing data base records, spread sheets or word processing files.