High-Quality Medical Image Compression Using Discrete Orthogonal Cosine Stockwell Transform and Optimal Integer Bit Allocated Quantization

  • Vikrant Singh Thakur
  • Kavita Thakur
  • Shubhrata Gupta
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10682)


Communication of the medical image and videos has now raised as a vital concern for the telediagnosis of critical diseases. Currently, JPEG and JPEG2k codecs are the default compression tool to facilitate their communication over band-limited channels. However, most often, the performance of these existing codecs is found poor particularly at the higher compression levels. Hence, this paper presents a new medical image compression codec to achieve high-quality compression of the medical images, especially at the higher compression levels. The proposed codec utilizes Discrete Orthogonal Cosine Stockwell Transform (DOCST) for the higher pixel decorrelation and the optimal integer bit allocation based quantization strategy for the efficient quantization of the DOCST coefficients. Further, to justify and validate the performance of the proposed codec an extensive performance analysis has been presented for six medical images of two different modalities. It is reported that the proposed codec outperforms the existing JPEG and JPEG2k codecs with significant quality gain for all the compression levels.


Medical image compression Image transform codecs DOCST transform Optimal integer bit allocation JPEG JPEG2k Image quality 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Vikrant Singh Thakur
    • 1
  • Kavita Thakur
    • 2
  • Shubhrata Gupta
    • 1
  1. 1.Department of Electrical EngineeringNational Institute of TechnologyRaipurIndia
  2. 2.S.O.S. in Electronics and PhotonicsPt. Ravishankar Shukla UniversityRaipurIndia

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