Optimal Bit Allocation Research Articles

Subband Weighting With Pixel Connectivity for 3-D Wavelet Coding

Performing optimal bit-allocation with 3-D wavelet coding methods is difficult because energy is not conserved after applying the motion-compensated temporal filtering (MCTF) process and the spatial wavelet transform. The problem cannot be solved by extending the 2-D wavelet coefficients weighting method directly and then applying the result to 3-D wavelet coefficients, since this approach does not consider the complicated pixel connectivity that results from the lifting-based MCTF process. In this paper, we propose a novel weighting method, which takes account of the pixel connectivity, to solve the problem and derive the effect of the quantization error of a subband on the reconstruction error of a group of pictures. We employ the proposed method on a 2-D + t structure with different temporal filters, namely the 5-3 filter and the 9-7 filter. Experiments on various coding parameters and sequences show that the proposed approach improves the bit-allocation performance over that obtained by using the weightings derived without considering the pixel connectivity in the MCTF process.

Equivalent Parallel Structure of Deinterlacer Banks and Its Application to Optimal Bit-Rate Allocation

In this paper, theoretical properties of deinterlacer banks are analyzed. Deinterlacer banks are novel filter banks in the sense that a progressive video sequence is separated into two progressive video sequences of a half frame rate and, furthermore, interlaced sequences are produced as intermediate data. Unlike the conventional filter banks, our deinterlacer banks are constructed in a way unique to multidimensional systems by using invertible deinterlacers, which the authors have proposed before. The system is a kind of shift-varying filter banks and it was impossible to derive the optimal bit-allocation control without any equivalent parallel filter banks. This paper derives an equivalent polyphase matrix representation of the whole system and its equivalent parallel structure, and then shows the optimal rate allocation for the deinterlacer banks. Some experimental results justify the effectiveness of the optimal rate allocation through our theoretical analysis.

An OFDM-TDMA/SA MAC Protocol with QoS Constraints for Broadband Wireless LANs

Orthogonal frequency division multiplexing (OFDM) is an important technique to support high speed transmission of broadband traffic in wireless networks, especially broadband wireless local area networks (LANs). Based on OFDM, a new multiple access scheme, called OFDM-TDMA with subcarrier allocation (OFDM-TDMA/SA), is proposed in this paper. It provides more flexibility in resource allocation than other multiple access schemes such as OFDM-TDMA, OFDM-frequency division multiple access (OFDM-FDMA), and orthogonal frequency division multiple access (OFDMA). With OFDM-TDMA/SA, a medium access control (MAC) is designed for broad-band wireless LANs. It optimizes bit allocation in subcarriers so that maximum bits are transmitted in each OFDM symbol under a frequency selective fading environment. The OFDM-TDMA/SA MAC protocol also supports three classes of traffic such as guaranteed, controlled-load, and best effort services. Based on the optimum subcarrier bit-allocation algorithm and considering heterogeneous QoS constraints of multimedia traffic, a hierarchical scheduling scheme is proposed to determine the subcarriers and time slots in which a mobile terminal can transmit packets. In such a way, the OFDM-TDMA/SA MAC protocol significantly increases system throughput in a frequency selective fading environment and guarantees QoS of multimedia traffic. Computer simulation is carried out to evaluate the performance of the OFDM-TDMA/SA MAC protocol. Results show that the new MAC protocol outperforms other MAC protocols for OFDM-based wireless LANs.

Robust stack-run coding for low bit-rate image transmission over noisy channels

We propose a multiresolution algorithm to jointly optimize a source coder and channel coder. The variable-rate source coder combines an optimal bit-allocation strategy and efficient stack-run coding. This compression scheme, concatenated with appropriate rate-compatible punctured convolutional codes, provides a competitive approach to state-of-the-art extensions of zerotree methods to noisy channels. Results show that under the assumption of almost zero probability of decoding error, the proposed scheme provides good performance for a lower complexity.

Uniform threshold TCQ with block classification for image transmission over noisy channels

A combined source-channel coding scheme without explicit error protection is proposed to transmit images over noisy channels. Major components of the proposed coding scheme include 2-D DCT with block classification, fixed-length uniform threshold trellis coded quantization, optimal bit-allocation algorithm, and noise reduction filters. The integration of these components allows us to organize the compressed bitstream in such a way that it is less sensitive to channel noise, and hence achieves data compression and error resilience at the same time. This paper reports our previous study by incorporating the block classification into the integrated scheme. Experimental results show that, in the case of noise-free channels and at the bit rate of 0.5 bpp, an improvement of 2.33 dB can be achieved with the classification. In the case of noisy channels, the gain decreases as the bit error rate increases. However, we can still achieve an average improvement of 0.46 dB, even for highly noisy channels with BER=0.1. Our proposed system uses no error protection, no synchronization codewords and no entropy coding. However, it shows a decent compression ratio and graceful degradation with respect to increasing channel errors.

Optimal subband coders of quantized multidimensional signals

A new general method is presented for the analysis of the effects of quantization and transmission noise in subband filter-bank multidimensional signal and image coders. Using general statistical noise characterization, the filter banks are obtained, which are optimal in the sense of minimizing the variance of the difference of the reconstructed signal from the original. It is shown that these are not identical to those achieving perfect reconstruction in lossless coding. A general method is described for the optimal selection of the synthesis filters if the analysis filters and quantizers are given. Assuming the use of these optimal synthesis filters, a method is then developed for the determination of the optimal analysis filters and the optimal bit-allocation to the subbands. The effects of quantization on perfect reconstruction filter-banks are analyzed next, and an explicit expression is determined for the quantizer noise-to-signal ratio for such banks. Given arbitrary quantizers, the analysis filters which are optimal in the sense of minimizing the output noise power are obtained. Finally, the jointly optimal selection is determined for the analysis filters and the bit allocations of the subbands. It is seen that this selection is identical to that determined for the theoretically optimal filter-banks.

Generalized rate-distortion optimization for motion-compensated video coders

This paper addresses jointly rate-distortion optimal selection of coding parameters in a general motion-compensated video coder. The general coder uses variable-block-size motion estimation and multimode residual coding. This is essentially the optimal bit-allocation problem for an individual frame at a given rate constraint. This paper not only gives the general formulation and solution using the Lagrange multiplier method and dynamic programming, but also demonstrates how the general theory can he adapted and applied to both an MPEG-like coder and a motion-compensated wavelet coder. Simulations demonstrate that both proposed coders outperform MPEG (TM5) by 0.7-1.3 dB at a variety of bit rates, with the gain provided by both better motion estimation and the joint-parameter optimization. The technique is applicable to MPEG-compliant coders with fixed block-size motion estimation and provides a gain of 0.5-0.7 dB over TM5. The optimization approach can also be applied to distortion-constrained coding, and therefore allows a fine tuning of either the rate or distortion to follow any desired profile.

Application of biorthogonal wavelet transform to the compression of ultraviolet-visible spectra

A wavelet transform (WT) based method was proposed to compress ultraviolet–visible (UV–vis) spectra from chemical and biochemical studies. These spectra were first transformed into different sub-bands which contain information on different scales and frequency bands. The biorthogonal filter banks (BFB) coupled with the circular (CE) or symmetric extension (SE) method were employed in the WT treatment. Differential pulse code modulation (DPCM) was applied to further reduce the storage space required for the scale coefficients which were generated from the WT treatment. Then, optimal bit allocation (OBA) procedure for data quantization coupled with variable length coding (VLC) was applied to these coefficients to minimize the root-mean-square difference (RMSD) between the original and reconstructed spectra. Both synthetic and experimental spectra were used in the study. Our results show that the performance of the proposed compression methods are better than those suggested in the previous studies.

Joint design of fixed-rate source codes and multiresolution channel codes

We propose three new design algorithms for jointly optimizing source and channel codes. Our optimality criterion is to minimize the average end-to-end distortion. For a given channel SNR and transmission rate, our joint source and channel code designs achieve an optimal allocation of bits between the source and channel coders. Our three techniques include a source-optimized channel code, a channel-optimized source code, and an iterative descent technique combining the design strategies of the other two codes. The joint designs use channel-optimized vector quantization (COVQ) for the source code and rate compatible punctured convolutional (RCPC) coding for the channel code. The optimal bit allocation reduces distortion by up to 6 dB over suboptimal allocations and by up to 4 dB relative to standard COVQ for the source data set considered. We find that all three code designs have roughly the same performance when their bit allocations are optimized. This result follows from the fact that at the optimal bit allocation the channel code removes most of the channel errors, in which case the three design techniques are roughly equivalent. We also compare the robustness of the three techniques to channel mismatch. We conclude the paper by relaxing the fixed transmission rate constraint and jointly optimizing the transmission rate, source code, and channel code.

Optimum Bit Allocation for a Given Signal-to-Noise Ratio in Transform Coding of Images

普通は, 画像の変換符号化においてビット配分は, 与えられたビットレートを一定にして量子化誤差を最小にするように決められる.しかしながら, 本稿では, 逆に与えられた量子化誤差が一定で, ビットレートを最小にするビット配分の解析的な式を求める.一般に, テレビ画像を伝送する時は前者の方が発生情報量が一定なので, 一定の周期の動作を確保するうえで有利であるが, 統計的性質の異なった静止画を伝送したり, メモリーに蓄積する場合は, 後者の方が画像の品質を保つうえで実際的である.本稿では, 各変換係数の分布はラプラス分布に従い, 交流分にはMAXの量子化器を用い, 量子化誤差はPanter-Diteの式に従うものとして, クーンタッカーの必要十分条件よりビット配分を求めた.このビット配分により計算機で実際に画像を量子化するシミュレーションを行った結果, SNRは, ほぼ設定値に等しくなった.これにより, 所望の品質 (SNR) に対する画像が得られる.