Name
Abstract | ||
|---|---|---|
Adaptive compression methods have been a key component of many proposed subband (or wavelet) image coding techniques. This paper deals with a particular type of adaptive subband image coding where we focus on the image coder's ability to adjust itself "on the fly" to the spatially varying statistical nature of image contents. This backward adaptation is distinguished from more frequently used forward adaptation in that forward adaptation selects the best operating parameters from a predesigned set and thus uses considerable amount of side information in order for the encoder and the decoder to operate with the same parameters. Specifically, we present backward adaptive quantization using a new context-based classification technique which classifies each subband coefficient based on the surrounding quantized coefficients. We couple this classification with online parametric adaptation of the quantizer applied to each class. A simple uniform threshold quantizer is employed as the baseline quantizer for which adaptation is achieved. Our subband image coder based on the proposed adaptive classification quantization idea exhibits excellent rate-distortion performance, in particular at very low rates. For popular test images, it is comparable or superior to most of the state-of-the-art coders in the literature. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1109/83.806617 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
image subband coding,adaptive quantization,image content,image coding,proposed adaptive classification quantization,popular test image,image subband,adaptive subband image,data compression,subband image coder,backward adaptive quantization,adaptive compression methods,image classification,online parametric adaptation,forward adaptation,backward adaptation,image coder,context-based classification technique,adaptive codes,context-based classification,adaptive compression method,image coding techniques,rate-distortion performance,uniform threshold quantizer,compaction,frequency,subband coding,image compression,testing,indexing terms,decoding,quantization | Computer vision,Pattern recognition,Image processing,Parametric statistics,Encoder,Sub-band coding,Artificial intelligence,Data compression,Quantization (signal processing),Contextual image classification,Mathematics,Wavelet | Journal |
Volume | Issue | ISSN |
8 | 12 | 1057-7149 |
Citations | PageRank | References |
32 | 9.39 | 24 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Y Yoo | 1 | 84 | 24.92 |
| Antonio Ortega | 2 | 4720 | 493.26 |
| B Yu | 3 | 33 | 9.73 |