Wavelet decomposition is a well-known technique to compress image data. Here, we have used wavelet decomposition to compress digital elevation models, DEM. The objectives for compressing DEMs are obtaining manageable and small data sets, and reducing data access time. In the paper, different aspects of wavelets as a base for data compression are described. The (de-)compression scheme consists o...

Ginger moxibustion is characterized by performing easily, activating local blood circulation, warming meridian and unblocking collateral obviously.In order to observe the therapeutic effects of ginger for swelling pain after COVID-19vaccines, 36 cases were randomly divided into 2 groups, whom 18 treated with hot compress. The results showed a cure rate 100% total effective in group, while 27.8%...

In this paper, we study the problem of compressing a data structure (e.g. tree, undirected and directed graphs) in an eecient way while keeping a similar structure in the compressed form. To date, there has been no proven optimal algorithm for this problem. We use the idea of building LZW tree in LZW compression to compress a binary tree generated by a stationary ergodic source in an optimal ma...

The art world uses the tradition of portraiture to semantically compress relevant information about their subjects into a single art work. We believe this tradition can be extended into the digital realm by the use of topic modeling to compress individuals’ information into generative data portraits. Data portraiture has strong implications for navigating large social spaces, collaborative syst...

Abstract-In this paper we will study the concept of image compression and study about the various technologies applied on the image compressio. Also highlight the benefits of the image compression .In this paper two technologies of image compression are highlighted they are lossless compression, lossy compression and various technology included in them. Image compression is a process of compres...

ABSTRACT The polyharmonic local cosine transform (PHLCT), presented by Yamatani and Saito in 2006, is a new tool for local image analysis and synthesis. It can compress and decompress images with better visual fidelity, less blocking artifacts, and better PSNR than those processed by the JPEG-DCT algorithm. Now, we generalize PHLCT to the high-dimensional case and apply it to compress the high-...