A Review on Wavelet-Based Image Compression Techniques

The world creates and feeds on huge chunks of storage space containing multimedia. Most part of this belongs to images. As technology is constantly growing, the sizes and the pixel density of these images are getting enhanced. Hence, efficient techniques are required to maintain their size and reusability. For example, in the field of medicine, highly detailed images requires storage of large quantities of digitized clinical data. Due to the bandwidth and storage limitations, these medical images must be compressed before transmission and storage. Diagnosis is effective only when compression techniques preserve all the relevant and important image information needed. Hence, image compression comes into the spotlight. The objective of compression is to reduce irrelevance and redundancy of the image data in order to be able to store or transmit data in an efficient form. There are basically two types of image compression: lossless and lossy. Lossless coding does not permit high compression ratios whereas lossy coding can achieve high compression ratio. Among the existing lossy compression schemes, transform coding is one of the most effective strategies. In the vicinity of this paper, the various coding techniques with their description and highlights of their merits and demerits are discussed. This can provide an insight to users on comparing and considering all the techniques and to choose the one based on requirement in hand.