DocumentCode :
179824
Title :
Image cellular automata coding based on resolution progressive experiments with color spaces and file formats
Author :
Claiboon, Phakphoom ; Wongthanavasu, Sartra
Author_Institution :
Dept. of Comput. Sci., Khon Kaen Univ., Khon Kaen, Thailand
fYear :
2014
fDate :
July 30 2014-Aug. 1 2014
Firstpage :
458
Lastpage :
462
Abstract :
Scalability or Progressive is a method used to reduce the quality used in Image Compression. There are several types of scalability: Quality, Resolution and Component. Each type is considered and calculated differently depending on purpose. In this research, we consider aspects of Resolution Progressive. Currently, the methods commonly used for this image encoding include Wavelet and Laplacian Pyramids. The objective is to maximize the quality of information that is encoded and to display the results in multiple resolutions. This paper presents an encoding method consisting of Reversible Cellular Automata and Intra-prediction. Reversible Cellular Automata methods are used for data conversion to adjust the resolution and Intra-prediction is applied to reduce redundant data that is to be compressed. Necessary experiments with color images are used to test the stability of the data after saving various image formats such as BMP and JPEG using the PSNR and SSIM performance measures. In this regard, the proposed method experiments with RGB color and BMP formats which provide more results than the other color space and file formats.
Keywords :
Laplace transforms; cellular automata; data compression; image coding; image colour analysis; image resolution; wavelet transforms; BMP image format; Intraprediction adjustment; JPEG image format; Laplacian pyramids; PSNR performance measure; SSIM performance measure; color spaces; component scalability; data conversion; data stability testing; file formats; image cellular automata coding; image compression; information quality maximization; quality reduction; quality scalability; redundant data reduction; resolution adjustment; resolution progressive experiments; resolution scalability; reversible cellular automata; wavelet pyramids; Computer science; Conferences; Decision support systems; Handheld computers; Image coding; PSNR; Intra-prediction; Resolution progressive; Reversible Cellular automata (RCA); Scalable image coding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Engineering Conference (ICSEC), 2014 International
Conference_Location :
Khon Kaen
Print_ISBN :
978-1-4799-4965-6
Type :
conf
DOI :
10.1109/ICSEC.2014.6978240
Filename :
6978240
Link To Document :
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