JOURNAL ARTICLE

<title>Coding of nonsmooth images in lossless manner</title>

Artur Przelaskowski

Year: 1999 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 3846 Pages: 432-440   Publisher: SPIE

Abstract

The considerations on effective lossless coding of non- smooth images are presented in this paper. Selection of the best not time consuming coding algorithms for a class of medical images is made a matter rather than completely new concept introduction. As a reference we consider the most efficient CALIC method, new lossless standard JPEG-LS and BTPC algorithm. Different methods of image scanning and 1D encoding are tested. Simple raster-scan data ordering followed by n-order arithmetic coding gives significant encoding efficiency for ultrasound images considered as a representative of the non-smooth image class. The lower bit rates could be achieved by additional statistical modeling in arithmetic coder based on the 12th order context quantized to one-order context. Therefore number of states in conditional probability model is reduced to overcome dilution problem. Finally, improved compression efficiency of non-smooth images in comparison to state-of-the-art CALIC algorithm is achieved. Average bit rate value is diminished over 30 percent. To compress smooth images the linear prediction scheme is incorporated for entire data redundancy reduction. The same model based on linear combination of adjacent pixels is used in prediction and entropy encoding steps. For smooth images our method performance is comparable to JPEG-LS and slightly worse than CALIC.

Keywords:
Arithmetic coding Lossless compression Entropy encoding Computer science Context-adaptive binary arithmetic coding Lossless JPEG Algorithm Data compression Lossy compression Context-adaptive variable-length coding Pixel Image compression Artificial intelligence Image processing Image (mathematics)

Metrics

1
Cited By
0.37
FWCI (Field Weighted Citation Impact)
4
Refs
0.60
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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