A New Image Compression Scheme Using Hyperanalytic Wavelet Transform and SPIHT

The amount of information that is handled by computers has grown exponentially over the past decades. Hence, the storage and transmission of the digital image component of Multimedia systems is a major problem. The amount of data required to present images at an acceptable level of quality is extremely large. High quality image data requires large amounts of storage space and transmission bandwidth, something which the current technology is unable to handle technically and economically. The success of wavelet techniques in many fields of signal and image processing was proved to be highly influenced by the properties of wavelet transforms used, mainly the shift invariance and the 88 D. Prathyusha Reddi et al directional selectivity. Unfortunately, the 2D discrete wavelet transform is shiftvariant and has a reduced directional selectivity. These disadvantages can be overcome if a complex wavelet transform is used. The Hyperanalytic Wavelet Transform (HWT) is quasi shift-invariant, it has a good directional selectivity, and a reduced degree of redundancy. The present work discusses the efficacy of HWT and how the properties of HWT are used for image compression. The results obtained are compared with DWT. Appreciable increase in PSNR along with compression ratio is obtained.