Image compression refers to convert data of more memory storage to the lesser one.
Image data compression becomes foremost method for reducing the data redundancy
to save more hardware area and transposal capacity. Image compression techniques
are mainly used in space and telehealth applications. Image decompression is to
give back the original image; it is an application to get much better image in terms
of quality or size and also original image are obtained from their compressed form.
Various algorithms for image compression/decompression techniques in previous
works for space and telehealth applications are: watermarking algorithm, clusteringbased
compression method, improved watershed transform method, Set partitioning
in hierarchical trees (SPHIT) algorithm, Discrete wavelet transform (DWT) with Bit
plane encoding (BPE), Content based adaptive scanning method, Adaptive lifting
DWT and modified SPIHT algorithm.
Keywords: image compression, image decompression, DWT with BPE, SPIHT,
watermarking, clustering.