Results 201 to 210 of about 11,899,310 (240)

Lossless Compression of DNA Microarray Images

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05), 2006
Microarray experiments are characterized by a massive amount of data, usually in the form of an image. Based on the nature of microarray images, we consider the microarray in terms of its structure and statistics. Based on the microarray image model, we propose a context-based method for lossless compression of microarray images using prediction by ...
Yong Zhang 0050, Rahul Parthe, Donald A. Adjeroh   +2 more
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On the JPEG model for lossless image compression

Data Compression Conference, 1992., 2003
The JPEG lossless arithmetic coding algorithm and a predecessor algorithm called Sunset both employ adaptive arithmetic coding with the context model and parameter reduction approach of Todd et al. The authors compare the Sunset and JPEG context models for the lossless compression of gray-scale images, and derive new algorithms based on the strengths ...
Glen G. Langdon Jr., A. Gulati, E. Seiler   +2 more
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An asymmetric lossless image compression technique

Proceedings., International Conference on Image Processing, 2002
While there exist many asymmetric techniques for the lossy compression of image data, most techniques reported for lossless compression of image data have been symmetric. In this paper we present a new lossless compression technique that is well suited for asymmetric applications.
Nasir D. Memon, Khalid Sayood
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Subaperture image segmentation for lossless compression

2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA), 2017
The paper proposes an image segmentation method for lossless compression of plenoptic images. Each light-field image captured by the plenoptic camera is processed to obtain a stack of subaperture images. Each subaperture image is encoded by using a gradient-base detector which classifies the image edges and designs refined contexts for an improved ...
Ionut Schiopu, Moncef Gabbouj, Alexandros Iosifidis, Bing Zeng 0001, Shuaicheng Liu   +4 more
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Nearly-lossless autoregressive image compression

Pattern Recognition Letters, 1999
Abstract A flexible accurate technique for improving image compression properties with linear image compressing transforms is presented. This is a reliable iterative algorithm for the nearly-lossless autoregressive (NLAR) compression of images, which permits control of errors produced in each pixel intensity while preserving the original image ...
Oleg S. Pianykh, John M. Tyler, Raj Sharman   +2 more
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Visually Lossless Compression of Stereo Images

2013 Data Compression Conference, 2013
With consumer-grade 3D displays becoming widely available, stereoscopic 3D imaging has received increased attention over the last few years. Since a left eye and a right eye image are contained in a stereo pair, stereoscopic imaging requires double the amount of data compared to 2D images. Therefore, efficient data compression techniques are especially
Hsin-Chang Feng, Michael W. Marcellin, Ali Bilgin   +2 more
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Lossless compression for three-dimensional images

SPIE Proceedings, 2004
We investigate and compare the performance of several three-dimensional (3D) embedded wavelet algorithms on lossless 3D image compression. The algorithms are Asymmetric Tree Three-Dimensional Set Partitioning In Hierarchical Trees (AT-3DSPIHT), Three-Dimensional Set Partitioned Embedded bloCK (3D-SPECK), Three-Dimensional Context-Based Embedded ...
Xiaoli Tang, William A. Pearlman
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An evolvable predictor for lossless image compression

2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353), 2003
This paper presents the adaptation via evolutionary techniques of a pixel predictor for lossless image compression. The pixel prediction is based on a linear combination of some neighbor pixels. The evolutionary algorithm selects the coefficients and the pixels involved in the pixel prediction.
Daniel León, Sina Balkir, Khalid Sayood
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Lossless and Near-Lossless Compression for Mammographic Digital Images

2006 International Conference on Image Processing, 2006
In this paper, a method for lossless and near lossless compression of large digital mammograms is proposed. This method is based on a predictive coder that uses integer-to-integer operations, and generates a two-layer embedded bit stream (i.e. near-lossless and refinement layer). The maximum tolerated pixel distortion is guaranteed in the near lossless
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Adaptive prediction for lossless image compression

Signal Processing: Image Communication, 2002
Abstract Lossless image compression is often performed through decorrelation, context modelling and entropy coding of the prediction error. This paper aims to identify the potential improvements to compression performance through improved decorrelation.
Marusic, Slaven., Deng, Guang.
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