Title :
ICA-Based Algorithms Applied to Image Coding
Author :
Narozny, Michel ; Barret, Michel
Author_Institution :
Signal Process. Syst. Team, SUPELEC, Metz
Abstract :
Recently, Narozny et al (2005) proposed a new viewpoint in variable high-rate transform coding. They showed that the problem of finding the optimal 1-D linear block transform for a coding system employing entropy-constrained uniform quantization may be viewed as a modified independent component analysis (ICA) problem. By adopting this new view-point, two new ICA-based algorithms, called GCGsup and ICAorth, were then derived for computing respectively the optimal linear transform and the optimal orthogonal transform. In this paper, we show that the transforms returned by GCGsup and ICAorth can achieve better visual image quality (better preservation of lines and contours) than the KLT and 2-D discrete cosine transform (DCT) when applied to the compression of well-known grayscale images.
Keywords :
Karhunen-Loeve transforms; discrete cosine transforms; image coding; independent component analysis; transform coding; 2D discrete cosine transform; ICA-based algorithms; KLT; entropy-constrained uniform quantization; grayscale images; image coding; independent component analysis; linear block transform; optimal orthogonal transform; variable high-rate transform coding; Discrete cosine transforms; Discrete transforms; Gray-scale; Image coding; Image quality; Independent component analysis; Karhunen-Loeve transforms; Quantization; Signal processing algorithms; Transform coding; DCT; KLT; Transform coding; image coding; independent component analysis;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0727-3
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2007.366087