A Natural Image Compression Approach Based on Independent Component Analysis and Visual Saliency Detection

2012 ◽  
Vol 6 (1) ◽  
pp. 646-649 ◽  
Author(s):  
Lijuan Duan ◽  
Chunxia Ke ◽  
Chunpeng Wu ◽  
Zhen Yang ◽  
Jun Miao
Keyword(s):  
Independent Component Analysis ◽  
Image Compression ◽  
Saliency Detection ◽  
Visual Saliency ◽  
Component Analysis ◽  
Independent Component ◽  
Natural Image ◽  
Visual Saliency Detection

A Natural Image Compression Approach Based on ICA and Visual Saliency Detection

2011 ◽  
Vol 128-129 ◽  
pp. 457-460
Author(s):  
Li Juan Duan ◽  
Chun Xia Ke ◽  
Chun Peng Wu ◽  
Zhen Yang ◽  
Jun Miao
Keyword(s):  
Image Compression ◽  
Saliency Detection ◽  
Similarity Index ◽  
Visual Saliency ◽  
Structural Similarity ◽  
Natural Image ◽  
Compression Method ◽  
Method Performance ◽  
Important Region ◽  
Visual Saliency Detection

In this paper, a natural image compression method is proposed based on independent component analysis (ICA) and visual saliency detection. The proposed compression method learns basis functions trained from data using ICA to transform the image at first; and then sets percentage of the zero coefficient number in the total transforming coefficients. After that, transforming coefficients are sparser which indicates further improving of compression ratio. Next, the compression method performance is compared with the discrete cosine transform (DCT). Evaluation through both the usual PSNR and Structural Similarity Index (SSIM) measurements showed that proposed compression method is more robust to DCT. And finally, we proposed a visual saliency detection method to detect automatically the important region of image which is not or low compressed while the other regions are highly compressed. Experiment shows that the method can guarantee the quality of important region effectively.

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