Hierarchical interpolation

Viergever, Max A.; Roos, Paul

doi:10.1109/51.195940

Cited by 16 publications

(6 citation statements)

References 20 publications

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“…A lossless coder that combined subsampling with hierarchical interpolation was proposed in Viergever and Roos (1993). The initial process performs very coarse subsampling on the image data.…”

Section: Subsampling Pyramid and Codersmentioning

confidence: 99%

Survey of progressive image transmission methods

Chee¹

1999

Int. J. Imaging Syst. Technol.

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Section: Subsampling Pyramid and Codersmentioning

confidence: 99%

Survey of progressive image transmission methods

Chee¹

1999

Int. J. Imaging Syst. Technol.

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“…Examples of transform methods applied in image compression are [1] Recently, methods based on the Wavelet Transform have been proposed [2] [3]. However, Wavelet-based methods can also be considered as multiresolution techniques.…”

Section: Introductionmentioning

confidence: 99%

“…In the majority of the methods, pixels values are first decorrelated, and then data is encoded using a variable length approach, such as Huffman or arithmetic coding. Image decorrelation methods can be divided into three categories [1]: transform methods, methods based on predictors, and multiresolution techniques.…”

Section: Introductionmentioning

confidence: 99%

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A lossless compression approach for mammographic digital images based on the Delaunay triangulation

Silva

Scharcanski

2005

IEEE International Conference on Image Processing 2005

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In this paper, a method for lossless compression of large digital mammograms is proposed. In order to efficiently remove the spatial redundancy from the mammographic images, we use a geometric predictor based on irregular sampling and the Delaunay Triangulation. The difference between the predicted and the original (i.e. the error image) is calculated and encoded using JPEG-LS approach. For faster convergence, we build the triangulation using the pixels most significant bits, and code separately the least significant bits using the PNG approach. Comparisons with other proposed approaches are based on a database of high-resolution digital mammograms. The preliminary results indicate that our method can offer average compression ratios 43%, 40%, 45%, and 25% higher than JPEG 2000, JPEG-LS, JPEG-lossless, and PNG, respectively.

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“…Multiresolution similar to pyramids techniques [8] utilized efficiently for medical image compression due to its simplicity, higher compression rates, fast and easy to implement [9]- [11]. Its implementation is generally composed of two basic steps filtering and decimation (i.e., sub-sampling) process, for more details see [12]- [14].…”

Section: Introductionmentioning

confidence: 99%

Lossless Compression of Medical Images using Multiresolution Polynomial Approximation Model

Al-Khafaji¹,

Al-Mahmood²

2013

IJCA

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In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques. General TermsMultiresolution and polynomial approximation within high synthetic coding architecture for lossless image compression.

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Hierarchical interpolation

Cited by 16 publications

References 20 publications

Survey of progressive image transmission methods

Survey of progressive image transmission methods

A lossless compression approach for mammographic digital images based on the Delaunay triangulation

Lossless Compression of Medical Images using Multiresolution Polynomial Approximation Model

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