JPEG 2000: Image Compression Fundamentals, Standards and Practice
JPEG 2000: Image Compression Fundamentals, Standards and Practice
LOCO-I: a low complexity, context-based, lossless image compression algorithm
DCC '96 Proceedings of the Conference on Data Compression
Context-Based Arithmetic encoding of 2D Shape Sequence
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
Lossy to lossless object-based coding of 3-D MRI data
IEEE Transactions on Image Processing
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
IEEE Transactions on Circuits and Systems for Video Technology
Shape-adaptive discrete wavelet transforms for arbitrarily shaped visual object coding
IEEE Transactions on Circuits and Systems for Video Technology
3-D wavelet coding of video with arbitrary regions of support
IEEE Transactions on Circuits and Systems for Video Technology
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This paper proposes an object-based, highly scalable, lossy-to-lossless coding approach for magnetic resonance (MR) images. The proposed approach, called OBHS-SPIHT, is based on the well known set partitioning in hierarchical trees (SPIHT) algorithm and supports both quality and resolution scalability. It progressively encodes each slice of the MR data set separately in a multiresolution fashion from low resolution to full resolution and in each resolution from low quality to lossless quality. To achieve more compression efficiency, the algorithm only encodes the main object of interest in the input data set, and ignores the unnecessary background. The experimental results show the efficiency of the proposed algorithm for multiresolution lossy-to-lossless MRI data coding. OBHS-SPIHT, is a very attractive coding approach for medical image information archiving and transmission applications especially over heterogeneous networks.