Utilizing Soft Information in Image Decoding

1
Utilizing Soft Information in Image Decoding

• Hannes Persson
• Karlstad

2
Outline

• Background
• JPEG2000
• Soft information
• Experiments
• Conclusions future work

3
Soft Information in Image Decoding

• General purpose
• Make end-points aware of channel conditions
• Reduce retransmissions
• Maximum a-posteriori (MAP) estimates
• Soft decoding
• Produced at the receiver
• Assume bits are independent and equally likely
• Transparent to the wireless system used
  (independent of modulation, coding)
• Reliability measure of the received bits
• Express the certainty of a bits value to be
  correct

4
Communication Layers

• Modification limited to the receiver
• Assumptions about underlying communication layers
• Overlook bit-errors in user data
• Support inter-layer communication to be able to
  forward soft information

Application - JPEG2000 Transport - TCP-L Network
- IP Data link Physical - log-MAP soft information
5
JPEG2000 Overview
Forward wavelet transform
Arithmetic encoder
Compressed data
Quantization
Inverse wavelet transform
Arithmetic decoder
Dequantization
Compressed data
6
Arithmetic Coder

• Arithmetic coder applied to subsets of
  transformed data - code-blocks
• Restricts the amount of data the arithmetic coder
  is exposed to
• Bit-errors is contained in the code-block
• No propagation to other code-blocks
• Error resilient mechanisms in JPEG2000
• Encoded at the transmitter
• Bit-error detection with the arithmetic decoder
• Bit-error will stop the decoding of a code-block
• Error concealment

7
Utilizing Soft Information

• Bit-error detection with the arithmetic decoder
• Soft information utilization attempts to correct
  bit-errors by iterative arithmetic decoding
• Heuristic algorithm that swaps potential
  erroneous bits
• Potential erroneous bits deduced from soft
  information
• Goal is to correct all bit-errors in the
  code-block
• At least make error concealment less frequent

8
Experimental Set-up

• Image code-block size - 4x4, 16x16, 32x32, 64x64
• 16-QAM modulation
• Signal to Noise power relation - 5-16 dB
• Image transmitted 30 times over the noisy channel
  (lena image)
• Received image decoded with 3 different decoders

AWGN channel simulation
9
6 dB
10
8 dB
11
8 dB
12
8 dB

• Baseline 12.2452 dB Baseline 15.5012 dB
  Modified 17.7354 dB
• (no mechanisms used) (utilizes
  mechanisms) (utilizes mechanisms
  soft info.)

13
10 dB
14
10 dB
15
10 dB

• Baseline 18.2799 dB Baseline 19.335 dB
  Modified 28.8897 dB
• (no mechanisms used) (utilizes
  mechanisms) (utilizes mechanisms
  soft info.)

16
12 dB
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Conclusion Future

• Soft information in image decoding
• High gain in image quality possible (8-12dB)
• Both PSNR and visually
• Improvements of 30 percent observed
• Impact of code-block size
• Future
• Enhance algorithm for finding erroneous bits
• Layer interaction for the soft information
  exchange
• Format on soft information
• Combine with TCP-L

18
Soft information in multimedia

• Multimedia standards already define error
  detection mechanisms
• Motion JPEG2000
• MPEG-4
• RVLC
• Soft information and iterative decoding
• Soft information already exists
• Implementation issue
• Computational overhead