Title
Embedded image coding based on Laplacian pyramids with quantization feedback
Abstract
In this paper, a multi-layer SNR-scalable error-bounded image encoder is achieved in the framework of Laplacian pyramids with quantization noise feedback, by exploiting an entropy-minimizing optimum quantization strategy, a content-driven decision rule based on an L∞ activity measure, and multistage quantizers to progressively upgrade quality at full scale. The resulting scheme yields intermediate versions with scale and SNR both increasing, and a further SNR scalability on the full resolution, with possibly lossless reconstruction, thereby expediting interactive browsing of remote data bases of images of any sizes and wordlength. The proposed encoder outperforms JPEG which does not possess all the above mentioned attractive characteristics.
Year
Venue
Keywords
1996
EUSIPCO
psnr,transform coding,scalability,correlation
Field
DocType
ISBN
Decision rule,Computer vision,Algorithm,Transform coding,JPEG,Encoder,Artificial intelligence,Quantization (image processing),Quantization (signal processing),Mathematics,Scalability,Lossless compression
Conference
978-888-6179-83-6
Citations 
PageRank 
References 
1
0.37
0
Authors
4
Name
Order
Citations
PageRank
Bruno Aiazzi127527.84
Stefano Baronti255950.87
Franco Lotti3747.20
Luciano Alparone490180.27