Integer wavelet transform for embedded lossy to lossless image compression

Reichel, J.; Menegaz, Gloria; Nadenau, Marcus J.; Kunt, M.

doi:10.1109/83.908504

Cited by 109 publications

(40 citation statements)

References 23 publications

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“…This can have an important impact on the computational cost when large amounts of data (as volumes) must be handled. Finally, it asymptotically reduces the computational complexity by a factor four [33], [34]. Due to the rounding operations, the integer coefficients are different from the corresponding true wavelet coefficients.…”

Section: Three-dimensional Integer Dwt Via Liftingmentioning

confidence: 99%

Lossy to lossless object-based coding of 3-D MRI data

Menegaz

Thiran

2002

IEEE Trans. on Image Process.

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Abstract-We propose a fully three-dimensional (3-D) object-based coding system exploiting the diagnostic relevance of the different regions of the volumetric data for rate allocation. The data are first decorrelated via a 3-D discrete wavelet transform. The implementation via the lifting steps scheme allows to map integer-to-integer values, enabling lossless coding, and facilitates the definition of the object-based inverse transform. The coding process assigns disjoint segments of the bitstream to the different objects, which can be independently accessed and reconstructed at any up-to-lossless quality. Two fully 3-D coding strategies are considered: embedded zerotree coding (EZW-3D) and multidimensional layered zero coding (MLZC), both generalized for region of interest (ROI)-based processing. In order to avoid artifacts along region boundaries, some extra coefficients must be encoded for each object. This gives rise to an overheading of the bitstream with respect to the case where the volume is encoded as a whole. The amount of such extra information depends on both the filter length and the decomposition depth. The system is characterized on a set of head magnetic resonance images. Results show that MLZC and EZW-3D have competitive performances. In particular, the best MLZC mode outperforms the others state-of-the-art techniques on one of the datasets for which results are available in the literature.

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Section: Three-dimensional Integer Dwt Via Liftingmentioning

confidence: 99%

Lossy to lossless object-based coding of 3-D MRI data

Menegaz

Thiran

2002

IEEE Trans. on Image Process.

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“…The observed oscillatory trend of the PSNR along the coordinate axis entails the analysis of both the rounding noise implied by integer lifting [18] and the quantization noise. Fig.…”

Section: Resultsmentioning

confidence: 98%

“…Third, it is computationally efficient. It can be shown that the lifting steps implementation asymptotically reduces the computational complexity by a factor 4 with respect to the classical filter-bank implementation [18]. Finally, the transformation can be implemented in-place, namely progressively updating the values of the original samples, without allocating auxiliary memory.…”

Section: The 3-d/2-d Multidimensional Layered Zero Coding (Mlzc) mentioning

confidence: 99%

Three-dimensional encoding/two-dimensional decoding of medical data

Menegaz

Thiran²

2003

IEEE Trans. Med. Imaging

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“…The SPIHT algorithm is affected by the characteristic oscillation of the PSNR with the slice index due to the rounding noise introduced by integer lifting. 7,8 Conversely JPEG2000 does not suffer from such shortcoming due to the post-compression rate distortion policy.…”

Section: Codingmentioning

confidence: 99%

An interactive toolbox for atlas-based segmentation and coding of volumetric images

et al. 2007

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Medical imaging poses the great challenge of having compression algorithms that are lossless for diagnostic and legal reasons and yet provide high compression rates for reduced storage and transmission time. The images usually consist of a region of interest representing the part of the body under investigation surrounded by a "background", which is often noisy and not of diagnostic interest. In this paper, we propose a ROI-based 3D coding system integrating both the segmentation and the compression tools. The ROI is extracted by an atlas based 3D segmentation method combining active contours with information theoretic principles, and the resulting segmentation map is exploited for ROI based coding. The system is equipped with a GUI allowing the medical doctors to supervise the segmentation process and eventually reshape the detected contours at any point. The process is initiated by the user through the selection of either one pre-defined reference image or one image of the volume to be used as the 2D "atlas". The object contour is successively propagated from one frame to the next where it is used as the initial border estimation. In this way, the entire volume is segmented based on a unique 2D atlas. The resulting 3D segmentation map is exploited for adaptive coding of the different image regions. Two coding systems were considered: the JPEG3D standard and the 3D-SPITH. The evaluation of the performance with respect to both segmentation and coding proved the high potential of the proposed system in providing an integrated, low-cost and computationally effective solution for CAD and PAC systems.

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Integer wavelet transform for embedded lossy to lossless image compression

Cited by 109 publications

References 23 publications

Lossy to lossless object-based coding of 3-D MRI data

Lossy to lossless object-based coding of 3-D MRI data

Three-dimensional encoding/two-dimensional decoding of medical data

An interactive toolbox for atlas-based segmentation and coding of volumetric images

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