Mesh-based scalable image coding with rate-distortion optimization

2000 ◽  
Author(s):  
Gwenaelle Marquant ◽  
Stephane Pateux ◽  
Claude Labit
Keyword(s):  
Image Coding ◽  
Rate Distortion ◽  
Rate Distortion Optimization

Wavelet-based Entropy Measure for Rate-Distortion Optimization in Image Coding

2010 ◽  
Vol 56 (1) ◽  
pp. 25-32
Author(s):  
J. Garcia-Alvarez ◽  
H. Führ ◽  
G. Castellanos-Domínguez
Keyword(s):  
Image Coding ◽  
Rate Distortion ◽  
Entropy Measure ◽  
Quality Level ◽  
Rate Distortion Optimization ◽  
Information Quantity ◽  
Wavelet Representation ◽  
Wavelet Space ◽  
Definition Of ◽  
Entropy Estimates

Wavelet-based Entropy Measure for Rate-Distortion Optimization in Image CodingA novel method for calculation of the entropy measure in wavelet space is proposed. This perceived-based entropy measure uses a Second Order Model entropy estimator, in which the occurrence of neighbors is considered in formulation. It has the intention to allow the implementation of a more suitable measure in coding processes and a relationship between the metric and the description of perceptual features. This method is used for the Rate-Distortion optimization in order to improve the bit-allocation coding algorithm, demonstrating that the wavelet-based entropy estimates a truncation step close to the target rate. The hypothesis is founded in the effect of distortion on the coefficient allocation. Because entropy measure is a close approximation of the conditional probability of image in multi-resolution space, it provides an adequate representation for the information of aDetailfeature. A definition of Detail-based homogeneity variance criteria is used for the information quantity - wavelet representation space, in order to find the image that fits a given Quality Level criteria. Experimental results are obtained for artificial and natural databases.

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