A Similar Structure Block Prediction for Lossless Image Compression

Abstract

 In image compression the main challenge is to efficiently encode and represent high frequency image structural components such as patterns, edges and textures. In this work, we develop an efficient image compression scheme based on similar structure block prediction. This so-called similar structure block prediction is motivated by motion prediction in video coding, attempting to find an optimal prediction of structure components within previously encoded image regions

Authors and Affiliations

C. S. Rawat, Seema , Seema G.Bhateja , Dr. Sukadev Meher

Keywords

Related Articles

Implementation of Session- State -Service -A Framework for P2P Network

 Peer-to-Peer systems have become, in a short period of time, one of the fastest growing and most popular applications. The decentralized and distributed nature of P2P systems leads to living aside the client-...

E-mail Spam Classification With Artificial Neural Network and Negative Selection Algorithm

 This paper apply neural network and spam model based on Negative selection algorithm for solving complex problems in spam detection. This is achieved by distinguishing spam from non-spam (self from non-self)....

Relational Permanence Routing Protocol under Video Transmission for MANET

 Video transport over ad hoc networks is more challenging than over other wireless networks. The wireless links in an ad hoc network are not very much error resilient and can go down frequently because of node m...

Collision Avoidance Radar Operated LC Substrate based MSP Antenna in Vehicular Systems

Road safety and precautionary measurement based instruments became part and parcel of the modern vehicular systems. Collision avoidance helps to prevent the vehicles from accidents and from unnecessary collision while th...

Download PDF file
  • EP ID EP97594
  • DOI -
  • Views 142
  • Downloads 0

How To Cite

C. S. Rawat, Seema, Seema G. Bhateja, Dr. Sukadev Meher (2011). A Similar Structure Block Prediction for Lossless Image Compression. International Journal of Computer Science and Communication Networks, 1(3), 222-226. https://europub.co.uk/articles/-A-97594