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Transform coding of images using trellis coded quantization
Michael W. Marcellin
Electrical and Computer Engineering
Optical Sciences
Applied Mathematics - GIDP
Research output
:
Contribution to journal
›
Conference article
›
peer-review
6
Scopus citations
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Dive into the research topics of 'Transform coding of images using trellis coded quantization'. Together they form a unique fingerprint.
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Keyphrases
Transform Coding
100%
Trellis-coded Quantization
100%
Scalar Quantization
50%
Entropy-constrained
33%
Fixation Rate
33%
Background Noise
16%
Fuzziness
16%
Monochromatic Image
16%
Constrained Design
16%
Code Structure
16%
Rate-constrained
16%
Blocking Artifacts
16%
Subjective Quality
16%
Noise Artifacts
16%
Peak Signal to Noise Ratio
16%
Computer Science
Transform Coding
100%
Coded Quantization
100%
Scalar Quantizer
50%
Subjective Quality
16%
Background Noise
16%
peak signal to noise ratio
16%
Engineering
Quantization (Signal Processing)
100%
Scalar Quantizer
50%
Fixed Rate
33%
Signal-to-Noise Ratio
16%
Monochrome Image
16%
Fuzziness
16%
Peak Signal
16%
Subjective Quality
16%