ROI soccer video compression using wavelet-domain block matching and EBCOT coding techniques in very low bit rate communication

Grailu, Hadi; Soltani, Roya; Akrami, Mohammadreza

doi:10.1109/pria.2013.6528430

Cited by 1 publication

(1 citation statement)

References 13 publications

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“…Embedded Block coding is another ROI based method, (Grailu et al, 2013) the main advantage of these method is to get a target compression ratio and need not perform multiple compression. But this method suffers from very high computational complexity.…”

Section: Related Workmentioning

confidence: 99%

Medical Image Compression Technique Using Listless Set Partitioning in Hierarchical Trees and Contextual Vector Quantization for Brain Images

Sridevi¹

2013

Journal of Computer Science

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A hybrid image compression techniques has been developed to compress medical images. Due to the extensive use of medical images like CT and MR scan, these medical imagery are stored for a longer period for the continuous monitoring of the patients and the amount of data associated with images is large and it occupies enormous storage capacity. So, the medical images need to be compressed to reduce the storage cost and for transmission without any loss. In this study, a hybrid method which combines the Listless Set Partitioning in Hierarchical Trees (LSPIHT) and the Contextual Vector Quantization (CVQ) method for the compression of brain images. Here, the region containing the most important information for diagnosis is called Region of Interest (ROI) and this is to be compressed with out any loss in the quality. In this method, the ROI is encoded separately using LSPIHT and the Back Ground region (BG) is encoded using CVQ. Finally, the two regions are merged together to get the reconstructed image. Our results show that the proposed method gives very good image quality for diagnosis without any degradable loss. The performance of the compression technique is evaluated using the parameters (CR, MSE, PSNR) and achieved better result compared to other existing methods. As a result, we strongly believe that using our method, we can overcome the limitations in storage and transmission of medical images that are produced day by day.

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Section: Related Workmentioning

confidence: 99%

Medical Image Compression Technique Using Listless Set Partitioning in Hierarchical Trees and Contextual Vector Quantization for Brain Images

Sridevi¹

2013

Journal of Computer Science

View full text Add to dashboard Cite

show abstract

ROI soccer video compression using wavelet-domain block matching and EBCOT coding techniques in very low bit rate communication

Cited by 1 publication

References 13 publications

Medical Image Compression Technique Using Listless Set Partitioning in Hierarchical Trees and Contextual Vector Quantization for Brain Images

Medical Image Compression Technique Using Listless Set Partitioning in Hierarchical Trees and Contextual Vector Quantization for Brain Images

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