Curvelets With New Quantizer For Image Compression

This paper emphasizes on designing of a novice quantizer that is more suitable for compressing images through curvelet transform This compression algorithm is tested on various images like plain textured and building images The results are compared with the existing techniques like curvelet with existing quatizer wavelet with existing quantizer and wavelet with proposed quantzer The proposed algorithm curvelets with proposed quantizer outperforms the existing techniques The performance is evaluated through visual clarity Peak Signal to Noise Ratio PSNR and compression metrics such as Compression ratio and Bit-rat

Seismic Data Compression using Wave Atom Transform

Seismic data compression SDC is crucially confronted in the oil Industry with large data volumes and Incomplete data measurements In this research we present a comprehensive method of exploiting wave packets to perform seismic data compression Wave atoms are the modern addition to the collection of mathematical transforms for harmonic computational analysis Wave atoms are variant of 2D wavelet packets that keep an isotropic aspect ratio Wave atoms have a spiky frequency localization that cannot be attained using a filter bank based on wavelet packets and offer a significantly sparser expansion for oscillatory functions than wavelets curvelets and Gabor atom