Image Compression: A Survey <s> SPIHT ALGORITHM <s> The authors carry out low bit-rate compression of multispectral images by means of the Said and Pearlman's SPIHT algorithm, suitably modified to take into account the interband dependencies. Two techniques are proposed: in the first, a three-dimensional (3D) transform is taken (wavelet in the spatial domain, Karhunen-Loeve in the spectral domain) and a simple 3D SPIHT is used; in the second, after taking a spatial wavelet transform, spectral vectors of pixels are vector quantized and a gain-driven SPIHT is used. Numerous experiments on two sample multispectral images show very good performance for both algorithms. <s> BIB001 </s> Image Compression: A Survey <s> SPIHT ALGORITHM <s> Image compression has been one of the main research topics in the field of image processing for a long time. The research usually focuses on compressing images that are visible to humans. The images being compressed are usually gray-level images or RGB color images. Recent advances in technology, however, enable the authors to make the detailed processing of spectral features in the images. Therefore, the compression of images with many spectral channels, called multispectral images, is required. Many methods used in traditional lossy image compression can be reused also in the compression of multispectral images. In this paper, a new combination of clustering spectra, manipulating spectral vectors, and encoding and decoding for multispectral images is presented. In the manipulation of the spectral vectors PCA, ICA, and wavelets are used. The approach is based on extracting relevant spectral information. Furthermore, some quantitative quality measures for multispectral images are presented. <s> BIB002 </s> Image Compression: A Survey <s> SPIHT ALGORITHM <s> A new cubic convolution spline interpolation (CCSI )for both one-dimensional (1-D) and two-dimensional (2-D) signals is developed in order to subsample signal and image compression data. The CCSI yields a very accurate algorithm for smoothing. It is also shown that this new and fast smoothing filter for CCSI can be used with the JPEG standard to design an improved JPEG encoder-decoder for a high compression ratio. <s> BIB003 </s> Image Compression: A Survey <s> SPIHT ALGORITHM <s> Advances in wavelet transforms and quantization methods have produced algorithms capable of surpassing the existing image compression standards like the Joint Photographic Experts Group (JPEG) algorithm. For best performance in image compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry. However, the design possibilities for wavelets are limited because they cannot simultaneously possess all of the desirable properties. The relatively new field of multiwavelets shows promise in obviating some of the limitations of wavelets. Multiwavelets offer more design options and are able to combine several desirable transform features. The few previously published results of multiwavelet-based image compression have mostly fallen short of the performance enjoyed by the current wavelet algorithms. This paper presents new multiwavelet transform and quantization methods and introduces multiwavelet packets. Extensive experimental results demonstrate that our techniques exhibit performance equal to, or in several cases superior to, the current wavelet filters. <s> BIB004 </s> Image Compression: A Survey <s> SPIHT ALGORITHM <s> The authors propose a highly scalable image compression scheme based on the set partitioning in hierarchical trees (SPIHT) algorithm. The proposed algorithm, called highly scalable SPIHT (HS-SPIHT), adds the spatial scalability feature to the SPIHT algorithm through the introduction of multiple resolution-dependent lists and a resolution-dependent sorting pass. It keeps the important features of the original SPIHT algorithm such as compression efficiency, full SNR scalability and low complexity. The flexible bitstream of the HS-SPIHT encoder can easily be adapted to various resolution requirements at any bit rate. The parsing process can be carried out on-the-fly without decoding the bitstream by a simple parser (transcoder) that forms a part of a smart network. The HS-SPIHT algorithm is further developed for fully scalable coding of arbitrarily shaped visual objects. The proposed highly scalable algorithm finds applications in progressive web browsing, visual databases and especially in image transmission over heterogeneous networks. <s> BIB005
Several modified SPIHT algorithms are also introduced for compressing multispectral images in the spectral dimension by implementing KLT or VQ for the purpose to take a strong interband dependency benefits that such images contains. On adaptive it is seems that 3-DSPIHT is more appropriate due to its lower complexity of design. Performance is much out class both when multispectral and hyper spectral images are considered. The comparison is also given with respect to other schemes BIB001 . The use of pixel based error measures is our proposed method with multispectral image more likely the spectrum reconstruction accuracy according to the pixels. Usually grey level or RGB images are being compressed. For images which are multispectral are presented for measures some quantitative quality BIB002 . The working performance of a custom hardware implementation is dramatically enhanced and with the slight adjustment in existing algorithm desired output can also achieved. With fixed order SPIHT thus the original algorithms PSNR curve is also matched (Fry and Hauck, 2005) . Highly scalable SPIHT combines the features of spatial scalability through the necessary details of the original SPIHT algorithm like scalability; compression efficiency and low complexity are also kept BIB005 . The error-tolerant SPIHT algorithm is discussed here implement simple modifications and extensions to the conventional SPIHT coder. In terms of computational complexity the ER-SPIHT organization adds little overhead to either the encoder or decoder. The use of RCPC and CRC concatenated coding does add considerably to the processing requirements, although the complexity is comparable with other error-correcting methods BIB003 . Analyzing texture mapping homogeneity and by incorporating reduction of speckle into compression scheme improvement of image compression and interpretation is gain. At start in hierarchical trees SPIHT classical set partition implements wavelet compression scheme and changes for controlling the speckle reduction rate using various schemes of encoding to homogeneous and non homogeneous scene area BIB004 .