Multispectral image compression for spectral and color reproduction based on lossy to lossless coding
Author(s) -
Kazuma Shinoda,
Yuri Murakami,
Masahiro Yamaguchi,
Nagaaki Ohyama
Publication year - 2009
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.838843
Subject(s) - multispectral image , rgb color model , artificial intelligence , computer science , lossy compression , computer vision , lossless compression , jpeg 2000 , encoder , color space , data compression , color depth , image compression , color image , mathematics , image processing , image (mathematics) , operating system
In this paper we propose a multispectral image compression based on lossy to lossless coding, suitable for both spectral and color reproduction. The proposed method divides a multispectral image data into two groups, RGB and residual. The RGB component is extracted from the multispectral image, for example, by using the XYZ Color Matching Functions, a color conversion matrix, and a gamma curve. The original multispectral image is estimated from RGB data encoder, and the difference between the original and the estimated multispectral images, referred as a residual component in this paper, is calculated in the encoder. Then the RGB and the residual components are encoded by JPEG2000, respectively a progressive decoding is possible from the losslessly encoded code-stream. Experimental results show that, although the proposed method is slightly inferior to JPEG2000 with a multicomponent transform in rate-distortion plot of the spectrum domain at low bit rate, a decoded RGB image shows high quality at low bit rate with primary encoding of the RGB component. Its lossless compression ratio is close to that of JPEG2000 with the integer KLT.
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