A refined modified read compression technique for efficient sharing of multimedia data


  • T Kavitha Osmania University
  • K Jaya Sankar Osmanaia University






Cloud Computing, Compression Technique, Huffman Code, Modified READ, Neural Network.


Compression technique expedites in solving many of the research problems for storage and sharing of multimedia data over the wireless channel. Many applications such as UIDAI (Unique Identification Authority of India) and Digi Locker adopts cloud platform. The digital data such as fingerprint, iris, driving license, school certificates are scanned, encrypted and stored in cloud platform. These applications require lossless compression. Modified Huffman (MH) encoding is the most preferred technique to achieve lossless compression. However, the existing MH encoding technique suffers due to numerous codewords of large bit lengths thus effecting performance. Modified READ (MR) and Machine learning techniques are used by the state-of-art technique compression algorithms to achieve better compression. However, they incur computation overhead. To improve the compression ratio and reduce the processing time, a Refined Modified READ (RMR) encoding scheme is presented, the encoding is done using Refined Huffman (RH) by encoding the pixels diagonally instead of encoding the pixels horizontally. Then the subsequent lines are encoded using RMR in parallel fashion and in both directions, which helps in reducing the computation time. Experimental outcome shows that RMR achieves significant improvement in compression ratio over its predecessor and as well as many of the state-of-art technique compression algorithms like Lempel-Ziv-Welch (LZW), Joint Bi-level Image Group 2 (JBIG2) and Neural network-based compression technique Levenberg–Marquardt (LM) back propagation algorithm.




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