Vol. 1 Issue 2
Year:2013
Issue:Jun-Aug
Title:Enhancing Efficiency of SPIHT Using HCC for Medical Image Sequences
Author Name:M. Ferni Ukrit and G.R. Suresh
Synopsis:
Medical image sequences are produced in enormous amount which requires a large storage capacity. These image sequences are of great importance, hence it is necessary to develop a system that produces high degree of compression while preserving the medical information. Lossless compression Technique is required to reduce the number of bits to store these image sequences and take less time to transmit over the network. This paper proposes a method that combines SPIHT with HCC to enhance the compression ratio. Inter-frame coding is used to exploit the correlation among image sequences. Initially SPIHT is applied with fast block matching process, Diamond Search. To enhance the efficiency of compression ratio a new scheme Head Code Compression is introduced. Results are compared in terms of Compression Ratio and Peak Signal-to-Noise Ratio with other state of art coding. Experimental results of our proposed methodology achieves 25% more reduction than the other state-of-the-art algorithms.
Year:2013
Issue:Jun-Aug
Title:Enhancing Efficiency of SPIHT Using HCC for Medical Image Sequences
Author Name:M. Ferni Ukrit and G.R. Suresh
Synopsis:
Medical image sequences are produced in enormous amount which requires a large storage capacity. These image sequences are of great importance, hence it is necessary to develop a system that produces high degree of compression while preserving the medical information. Lossless compression Technique is required to reduce the number of bits to store these image sequences and take less time to transmit over the network. This paper proposes a method that combines SPIHT with HCC to enhance the compression ratio. Inter-frame coding is used to exploit the correlation among image sequences. Initially SPIHT is applied with fast block matching process, Diamond Search. To enhance the efficiency of compression ratio a new scheme Head Code Compression is introduced. Results are compared in terms of Compression Ratio and Peak Signal-to-Noise Ratio with other state of art coding. Experimental results of our proposed methodology achieves 25% more reduction than the other state-of-the-art algorithms.
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