learning image features to encode visual information (life-vision)
Post on 22-Mar-2016
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LEARNING IMAGE FEATURES TO ENCODE VISUAL INFORMATION
(LIFE-VISION)
Kick-off meeting28/01/2013
VISUALLY LOSSLESS CODING
LIFE-VISION
Visibility thresholds
VISUALLY LOSSLESS CODING
LIFE-VISION
Visibility thresholds
VISUALLY LOSSLESS CODING
LIFE-VISION
Visibility thresholds
VISUALLY LOSSLESS CODING
LIFE-VISION
Visibility thresholds
VISUALLY LOSSLESS CODING
LIFE-VISION
Visibility thresholds
VISUALLY LOSSLESS CODING
LIFE-VISION
Current methods: focused on the encoding process
JPEG2000 codestream
Research purpose: extract a visually lossless image from a JPEG2000 codestream
EMBEDDED QUANTIZATION
LIFE-VISION
0 W
EMBEDDED QUANTIZATION
LIFE-VISION
uniform scalar deadzone quantization (USDQ)
0 W
EMBEDDED QUANTIZATION
LIFE-VISION
bitplane coding (BPC)
0 Wemit 0 emit 1
EMBEDDED QUANTIZATION
LIFE-VISION
bitplane coding (BPC)
0 W0 1 0 1
EMBEDDED QUANTIZATION
LIFE-VISION
bitplane coding (BPC)
0 W0 10 10 10 1
WHY IS USDQ+BPC SO POPULAR ?
1) is convenient for current hardware2) achieves competitive coding performance3) many works aimed to improve efficiency
IS USDQ+BPC OPTIMAL FOR LOSSY IMAGE CODING ?
EMBEDDED QUANTIZATION
LIFE-VISION
0 W
0 W
T1
emit 0 emit 1
GENERAL EMBEDDED QUANTIZATION (GEQ)
EMBEDDED QUANTIZATION
LIFE-VISION
0 W
0 W
T1
0 1
T2
GENERAL EMBEDDED QUANTIZATION (GEQ)
EMBEDDED QUANTIZATION
LIFE-VISION
0 W
0 W
T1 T2
0 1
T3
GENERAL EMBEDDED QUANTIZATION (GEQ)
EMBEDDED QUANTIZATION
LIFE-VISION
0 W
0 W
GENERAL EMBEDDED QUANTIZATION (GEQ)
EMBEDDED QUANTIZATION
LIFE-VISION
0 W
0 W
different thresholds: /W
quantizers with K stages: )!/(! K
GENERAL EMBEDDED QUANTIZATION (GEQ)
EMBEDDED QUANTIZATION
LIFE-VISION
0 W
GENERAL EMBEDDED QUANTIZATION (GEQ)
0 W
different thresholds: /W
quantizers with K stages: )!/(! K
Example:
200W1
3K 4K 5K 6K610 7.9 910 1.5 910 304.3 1210 59.3
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