Aviris Hyperspectral Images Compression Using 3d Spiht Algorithm

Hyperspectral Image Compression Using 3d Spiht, Speck and Bezw Algorithms

Band Clustering for the Lossless Compression of AVIRIS Hyperspectral Images

Hyperspectral images can be efficiently compressed through a linear predictive model, as for example the one used in the SLSQ algorithm. In this paper we exploit this predictive model on the AVIRIS images by individuating, through an off-line approach, a common subset of bands, which are not spectrally related with any other bands. These bands are not useful as prediction reference for the SLSQ...

Medical Images Compression Using Modified SPIHT Algorithm and Multiwavelets Transformation

Recently, the wavelet transform has emerged as a cutting edge technology within the field of image compression research. Wavelet methods involve overlapping transforms with varying-length basis functions. This overlapping nature of the transform alleviates blocking artifacts, while the multi-resolution character of the wavelet decomposition leads to superior energy compaction and perceptual qua...

Color Image Compression using SPIHT Algorithm

In recent years there has been an astronomical increase in the usage of computers for a variety of tasks. With the advent of digital cameras, one of the most common uses has been the storage, manipulation, and transfer of digital images. The files that comprise these images, however, can be quite large and can quickly take up precious memory space on the computer’s hard drive. In multimedia app...

Effective Compression in Digital Images with SPIHT Algorithm and Entropy

Image compression is achieved by removing data redundancy while preserving information content. SPIHT is computationally very fast and among the best image compression algorithms known today. According to statistic analysis of the output binary stream of SPIHT encoding, propose a simple and effective method combined with Entropy for further compression that saves a lot of bits in the image data...