Rank-based image transformation for entropy coding efficiently

In this paper, we introduce a rank-based image transformation which is pre-processing method for gray-level images to be compressed more efficiently by entropy encoder. Before entropy encoding a stream of gray-level values in an image, the proposed method counts co-occurrence frequencies for neighbo...

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Bibliographic Details
Published inFourth Annual ACIS International Conference on Computer and Information Science (ICIS'05) pp. 478 - 482
Main Authors Deuk-Su Han, Myung-Jae Lee, Kang-Soo You, Jang, E.S., Hoon-Sung Kwak
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Bit rate
Digital arithmetic
Digital images
Electronic mail
Entropy coding
Frequency
Gray-scale
Image coding
Image converters
Pixel
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Summary:In this paper, we introduce a rank-based image transformation which is pre-processing method for gray-level images to be compressed more efficiently by entropy encoder. Before entropy encoding a stream of gray-level values in an image, the proposed method counts co-occurrence frequencies for neighboring pixel values. Then, it replaces each pairs of adjacent gray values with particular ordered number based on the investigated co-occurrence frequencies. Finally, the method transmits the adjusted data which has ordered number to entropy encoder. Because statistical characteristic is more enhanced by this preprocessing step, it is possible to improve performance of entropy coding. From the simulation result using 8 bits gray-scale images, it is verified that the proposed method can reduce bit rate by up to 37.85% than plain entropy coders.
Bibliography:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
content type line 25
ISBN:9780769522968
0769522963
DOI:10.1109/ICIS.2005.106