Progressive Image Compression Analysis Using Wavelet Transform

摘要

With the use of digital cameras, requirements for storage, manipulation, and transfer of digital images has grown explosively. These images can be very large in size and can occupy a lot of memory, so compression of images is required for efficient transmission and storage of images. Image data comprise of a significant portion of the multimedia data and they occupy the major portion of the channel bandwidth for multimedia communication. Therefore development of efficient techniques for image compression has become quite necessary. The design of data compression schemes involves trade-offs among various factors, including the degree of compression, the amount of distortion introduced (if using a lossy compression scheme) and the computational resources required for compressing and decompressing of images. Wavelet based compression methods, when combined with SPIHT (Set Partitioning in Hierarchical Trees) algorithm gives high compression ratio along with appreciable image quality (like lossless). SPIHT belongs to the next generation of wavelet encoders, employing more sophisticated coding. In fact, SPIHT exploits the properties of the wavelet-transformed images to increase its efficiency. Progressive image compression methods are more efficient than conventional wavelet based compression methods it gives the facility to user choose the best compressed image which does not have recognizable quality loss