5 research outputs found
Estimating Watermarking Capacity in Gray Scale Images Based on Image Complexity
Capacity is one of the most important parameters in image watermarking. Different works have been done on this subject with different assumptions on image and communication channel. However, there is not a global agreement to estimate watermarking capacity. In this paper, we suggest a method to find the capacity of images based on their complexities. We propose a new method to estimate image complexity based on the concept of Region Of Interest (ROI). Our experiments on 2000 images showed that the proposed measure has the best adoption with watermarking capacity in comparison with other complexity measures. In addition, we propose a new method to calculate capacity using proposed image complexity measure. Our proposed capacity estimation method shows better robustness and image quality in comparison with recent works in this field
Nested turbo codes for the costa problem
Driven by applications in data-hiding, MIMO broadcast channel coding, precoding for interference cancellation, and transmitter cooperation in wireless networks, Costa coding has lately become a very active research area. In this paper, we first offer code design guidelines in terms of source- channel coding for algebraic binning. We then address practical code design based on nested lattice codes and propose nested turbo codes using turbo-like trellis-coded quantization (TCQ) for source coding and turbo trellis-coded modulation (TTCM) for channel coding. Compared to TCQ, turbo-like TCQ offers structural similarity between the source and channel coding components, leading to more efficient nesting with TTCM and better source coding performance. Due to the difference in effective dimensionality between turbo-like TCQ and TTCM, there is a performance tradeoff between these two components when they are nested together, meaning that the performance of turbo-like TCQ worsens as the TTCM code becomes stronger and vice versa. Optimization of this performance tradeoff leads to our code design that outperforms existing TCQ/TCM and TCQ/TTCM constructions and exhibits a gap of 0.94, 1.42 and 2.65 dB to the Costa capacity at 2.0, 1.0, and 0.5 bits/sample, respectively
Source-channel coding for robust image transmission and for dirty-paper coding
In this dissertation, we studied two seemingly uncorrelated, but conceptually
related problems in terms of source-channel coding: 1) wireless image transmission
and 2) Costa ("dirty-paper") code design.
In the first part of the dissertation, we consider progressive image transmission
over a wireless system employing space-time coded OFDM. The space-time coded
OFDM system based on a newly built broadband MIMO fading model is theoretically
evaluated by assuming perfect channel state information (CSI) at the receiver for
coherent detection. Then an adaptive modulation scheme is proposed to pick the
constellation size that offers the best reconstructed image quality for each average
signal-to-noise ratio (SNR).
A more practical scenario is also considered without the assumption of perfect
CSI. We employ low-complexity decision-feedback decoding for differentially space-
time coded OFDM systems to exploit transmitter diversity. For JSCC, we adopt a
product channel code structure that is proven to provide powerful error protection and
bursty error correction. To further improve the system performance, we also apply
the powerful iterative (turbo) coding techniques and propose the iterative decoding
of differentially space-time coded multiple descriptions of images.
The second part of the dissertation deals with practical dirty-paper code designs. We first invoke an information-theoretical interpretation of algebraic binning and
motivate the code design guidelines in terms of source-channel coding. Then two
dirty-paper code designs are proposed. The first is a nested turbo construction based
on soft-output trellis-coded quantization (SOTCQ) for source coding and turbo trellis-
coded modulation (TTCM) for channel coding. A novel procedure is devised to
balance the dimensionalities of the equivalent lattice codes corresponding to SOTCQ
and TTCM. The second dirty-paper code design employs TCQ and IRA codes for
near-capacity performance. This is done by synergistically combining TCQ with IRA
codes so that they work together as well as they do individually. Our TCQ/IRA
design approaches the dirty-paper capacity limit at the low rate regime (e.g., < 1:0
bit/sample), while our nested SOTCQ/TTCM scheme provides the best performs so
far at medium-to-high rates (e.g., >= 1:0 bit/sample). Thus the two proposed practical
code designs are complementary to each other