Low Bit Rate Underwater Video Image Compression and Coding Method Based on Wavelet Decomposition

In view of the limited bandwidth of underwater video image transmission,a low bit rate underwater video compression coding method is proposed.Based on the preprocessing process of wavelet transform and coefficient down-sampling,the visual redundancy of underwater image is removed and the computational coefficients and coding bits are reduced.At the same time,combined with multi-level wavelet decomposition,inter frame motion compensation,entropy coding and other methods,according to the characteristics of different types of frame image data,reduce the number of calculations and improve the coding efficiency.The experimental results show that the reconstructed image quality can meet the visual requirements,and the average compression ratio of underwater video can meet the requirements of underwater acoustic channel transmission rate.

An Improved SPIHT Algorithm for Image Compression in Low Bit Rate

Aiming at shortage of the SPIHT algorithm, an improved image compression algorithm is proposed, in order to overcome the shortcomings of decoding image quality and coding time, LS9/7 lifting wavelet transform is adopted. According to the characteristics of the human visual system (HVS), the scanning mode and the method to determine the threshold of algorithm are changed to improve the quality of reconstruction image. On the question of repeating scan of SPIHT algorithm, using maximum list thought, greatly reduce the computation and save operating time. The experimental results have proved that the improved algorithm of image decoding time and the quality of reconstruction images are better than the original algorithm , especially in the case of low bit rate.

Very Low Bit-Rate Video Coding Based on Wavelet Transform

Two video coding schemes based on wavelet transform achieving very low bit rate are presented in this paper. The first is a hybrid motion compensated wavelet transform(MC WT)system which behaves better at very low bit rates than the block DCT residual coder. The second is a new efficient coding system based on a simple frame differencing wavelet transform(FD WT)which performs well in both PSNR and visual quality with substantially reduced complexity.

3-D Wavelet Transform for Very Low Bit-Rate Video Coding

A new improved Goh's 3 D wavelet transform(WT) coding scheme is presented in this paper. The new scheme has great advantages including a simple code structure, low computation cost and good performance in PSNR, compression ratios and visual quality of reconstructions, when compared to the other existing 3 D WT coding methods and the 2 D WT based coding methods. The new 3 D WT coding scheme is suitable for very low bit rate video coding.

Very Low Bit Rate Video Coding Using Motion Compensated 3 D Wavelet Transform

A new motion compensated 3 D wavelet transform (MC 3DWT) video coding scheme is presented in this paper. The new coding scheme has a good performance in average PSNR, compression ratio and visual quality of reconstructions compared with the existing 3 D wavelet transform (3DWT) coding methods and motion compensated 2 D wavelet transform (MC WT) coding method. The new MC 3DWT coding scheme is suitable for very low bit rate video coding.

Variable Bit Rate Fuzzy Control for Low Delay Video Coding

Rate control plays a critical role in achieving perceivable video quality under a variable bit rate,limited buffer sizes and low delay applications.Since a rate control system exhibits non-linear and unpredictable characteristics,it is difficult to establish a very accurate rate-distortion(R-D)model and acquire effective rate control performance.Considering the excellent control ability and low computing complexity of the fuzzy logic in non-linear systems,this paper proposes a bitrate control algorithm based on a fuzzy controller,named the Fuzzy Rate Control Algorithm(FRCA),for All-Intra(AI)and low-delay(LD)video source coding.Contributions of the proposed FRCA mainly consist of four aspects.First,fuzzy logic is adopted to minimize the deviation between the actual and the target buffer size in the hypothetical reference decoder(HRD).Second,a fast lookup table is employed in fuzzy rate control,which reduces computing cost of the control process.Third,an input domain determination scheme is proposed to improve the precision of the fuzzy controller.Fourth,a novel scene change detection is introduced and integrated in the FRCA to adaptively adjust the Group-of-Pictures(GOP)length when the source content fluctuates.The FRCA can be transplanted and implemented in various industry coders.Extensive experiments show that the FRCA has accurate variable bit-rate control ability and maintains a steady buffer size during the encoding processes.Compared with the default configuration encoding under AI and LD,the proposed FRCA can achieve the target bit rates more accurately in various classical encoders.

AVariablebitrateVideoCodingSchemeBasedonMorphologicalOperationsforATMNetworks

ＡＶａｒｉａｂｌｅｂｉｔｒａｔｅＶｉｄｅｏＣｏｄｉｎｇＳｃｈｅｍｅＢａｓｅｄｏｎＭｏｒｐｈｏｌｏｇｉｃａｌＯｐｅｒａｔｉｏｎｓｆｏｒＡＴＭＮｅｔｗｏｒｋｓＣｈｅｎＨｕｉｆａｎｇＤａｉＷｅｎｑｉＱｉｕＰｅｉｌｉａｎｇ（ＩｎｓｔｉｔｕｔｅｏｆＩｎｆｏ...

A rate control scheme for H.264 video under low bandwidth channel

The dilemma of the quantization parameter (QP) being involved in both rate control and rate-distortion optimization (RDO) prevents using the traditional rate control scheme. Although some rate control schemes are proposed to circumvent the dilemma, the inaccurate prediction model and improper bit allocation deter H.264 application on low bandwidth channel. To resolve this issue, this paper proposes a novel rate control scheme by considering the macroblock (MB) encoding complexity variation and buffer variation and by exploiting the spatio-temporal correlation sufficiently well. Simulations showed that this scheme improves the perceptual quality of the pictures with similar or smaller PSNR deviations when compared to that of rate control in JVT-O016.

Frame-layer bit allocation for multi-view video coding based on frame complexity estimation

Current multi-view video coding （MVC） reference model in joint video team （JVT） does not provide efficient rate control schemes. This paper presents a rate control algorithm for MVC by improving the quadratic rate-distortion （R-D） model. We reasonably allocate bit-rate among views based on the correlation analysisl The proposed algorithm consists of three levels to control the rate bits more accurately, of which the frame layer allocates bits according to the frame complexity and the temporal activity. Extensive experiments show that the proposed algorithm can control the bit rate efficiently.

Edge Oriented Compression Coding on Image Sequence

An edge oriented image sequence coding scheme is presented. On the basis of edge detecting, an image could be divided into the sensitized region and the smooth region. In this scheme, the architecture of sensitized region is approximated with linear type of segments. Then a rectangle belt is constructed for each segment. Finally, the gray value distribution in the region is fitted by normal forms polynomials. The model matching and motion analysis are also based on the architecture of sensitized region. For the smooth region we use the run length scanning and linear approximating. By means of normal forms polynomial fitting and motion prediction by matching, the images are compressed. It is shown through the simulations that the subjective quality of reconstructed picture is excellent at 0.0075 bit per pel.

A Modified Block Matching Motion Estimation Algorithm for the Very Low Bit-Rate video Coding

Block matching motion estimation techniques have been widely used in video coding applications. However, they also show their deficiency in the coherence of motion vectors and antinoise ability. This paper proposes a modified algorithm which can adopt any one of existing search algorithms and pays more attention to the correlation of neighboring blocks.It will be shown that the proposed algorithm is simple and significantly reduces the computational complexity. Simulation results also show that this algorithm improves the smoothness of the motion field, hence reducing the cost to code the motion vectors while keeping good performance comparable with the conventional block matching motion estimation algorithm.

基于模糊量化和2 bit深度像素的运动估计算法

提出了一种2 bit深度像素的运动估计算法。首先,将像素深度的降采样过程形式化为区间分划和区间映射2个步骤,其中前者为多对一映射,决定着运动估计性能,后者为一一映射;其次,提出一种非均匀量化方法求解区间分划的3个初始阈值,并利用隶属度函数对初始阈值细化,从而克服信号噪声等因素导致的初始阈值周围像素值的误匹配;再次,讨论了适用于2 bit深度像素运动估计的误差度量准则,进而提出了基于模糊量化和2 bit深度像素的运动估计算法;最后,借助信号自相关函数,建立比特深度转换误差—运动向量精度模型来估计该算法所能达到的预测精度。实验结果证明,对于多种类型的视频序列,尤其是场景细节和物体运动比较复杂者,该算法始终能保持较高的估计精度,运动补偿的平均峰值信噪比较之传统2 bit深度像素的运动估计提高0.27 dB。

一种基于混合MELP/CELP的4 kbit/s声码器

利用混合激励线性预测(mixed excitation linear prediction,MELP)算法和码激励线性预测(code excitation linear prediction,CELP)算法的优点,提出了一种混合MELP/CELP语音编码模型。编码端对强浊音帧采用MELP编码,对弱浊音帧和清音帧进行CELP编码。MELP编码器采用相位对齐技术提取强浊音帧的相位参数,解决了合成语音与原始语音在时间上不同步的问题。对实现的4 kbit/s混合MELP/CELP声码器进行客观MOS(mean opinion score)值和主观DRT(diagnostic rhythm test)清晰度测试,结果表明,该声码器的合成语音具有较高的可懂度和清晰度。

More efficient ground truth ROI image coding technique: implementation and wavelet based application analysis

In this paper, more efficient, low-complexity and reliable region of interest （ROI） image codec for compressing smooth low texture remote sensing images is proposed. We explore the efficiency of the modified RO! codec with respect to the selected set of convenient wavelet filters, which is a novel method. Such ROI coding experiment analysis representing low bit rate lossy to high quality lossless reconstruction with timing analysis is useful for improving remote sensing ground truth surveillance efficiency in terms of time and quality. The subjective [i.e. fair, five observer （HVS） evaluations using enhanced 3D picture view Hyper memory display technology] and the objective results revealed that for faster ground truth ROI coding applications, the Symlet-4 adaptation performs better than Biorthogonal 4.4 and Biorthogonal 6.8. However, the discrete Meyer wavelet adaptation is the best solution for delayed ROI image reconstructions.

OpenFlow网络中可伸缩视频的自适应传输算法

针对Open Flow网络中的自适应视频传输问题,提出一种可伸缩视频自适应传输算法。在Open Flow网络中,路由器的控制面被分离,由控制器观测可以得到网络的带宽变化。采用自回归模型,根据前一段时间的网络状况预测网络带宽在未来一段时间内的变化情况,控制器根据预测结果决策并告知客户端动态改变请求的视频层数。实验结果表明,该算法在保证较低中断的同时,能够准确地预测网络变化,提高视频播放质量。

Study of adaptive modulation and LDPC coding in multicarrier systems

An adaptive modulation （AM） algorithm is proposed and the application of the adapting algorithm together with low-density parity-check （LDPC） codes in multicarrier systems is investigated. The AM algorithm is based on minimizing the average bit error rate （BER） of systems, the combination of AM algorithm and LDPC codes with different code rates （half and three-fourths） are studied. The proposed AM algorithm with that of Fischer et al is compared. Simulation results show that the performance of the proposed AM algorithm is better than that of the Fischer＇s algorithm. The results also show that application of the proposed AM algorithm together with LDPC codes can greatly improve the performance of multicarrier systems. Results also show that the performance of the proposed algorithm is degraded with an increase in code rate when code length is the same.

基于尺度特征融合的极低比特率三维复杂图像无损压缩

由于三维复杂图像具有高维度和大规模的特点,且极低比特率下容易导致细节丢失和失真增强,使得三维复杂图像的编码较为复杂。因此,提出基于尺度特征融合的极低比特率三维复杂图像无损压缩方法。利用各向异性扩散与垂直扩散处理三维复杂图像,增强图像边缘信息。采用四叉树算法,建立自适应分块机制,按照图像细节复杂程度划分多个图像块。构建残差网络、反卷积网络结构的残差变换模块,融合图像多尺度特征,输出压缩图像。引入高分辨率累加器和计数器,实现压缩图像无损编码,实现完整的三维复杂图像无损压缩。实验结果表明:应用基于尺度特征融合的新型无损压缩方法后,图像压缩重构结果的信息熵达到了30,实现了压缩图像质量的提升。

语义引导的水下带噪语音通信

针对狭窄带宽的多径水声信道和信源噪声干扰导致的退化语音,提出了一种语义引导的水下带噪语音通信系统,实现了噪声环境下高效鲁棒的语音通信。首先,通过引入语音去噪网络降低了信源噪声的影响。系统通过传输语音的语义信息,实现了语音信号的极限压缩。针对信道噪声对数据的损伤,使用语义纠错模块在接收端对退化的语义特征进纠错,从而提高重建语音的可理解性。此外,结合多阶段训练策略的退化知情模型进一步增强所提方法在水声信道中的鲁棒性和泛化性。最后,在语音重建过程中使用多感受野-挤压激励融合模块以捕获语义特征中的全局语义信息,优化重建语音的可理解性。仿真实验结果表明,该方法在极低码率压缩的情况下,在复杂的噪声环境和不同的水声信道条件中,具有良好的重建性能。

无人机航拍视频码率控制算法优化

高效率视频编码(HEVC)在实际应用中很难满足无人机航拍领域的需求。针对此问题,提出一种基于缓冲区状态及视频显著性的码率控制算法。对预处理后的帧进行颜色、纹理特征提取,并采用log-Gabor滤波器对其进行特征滤波,得到当前帧的显著图;计算每帧和每个最小单元(CTU)的显著性权重;以帧的显著性权重和缓冲区状态指导帧层比特分配,以CTU的显著性权重指导CTU层比特分配。实验结果表明,提出的算法可以在缓冲区维持在一个平稳状态的前提下,提高0.61 dB视频显著区域的峰值信噪比,更适用于无人机航拍的场景。

基于增强型多尺度残差生成对抗网络的图像压缩

为解决低码率下更符合人类视觉感知的图像压缩,提出一种基于增强型多尺度残差生成对抗网络的有损压缩方法。在网络框架的自动编码器中,使用一种结构上改进的增强型多尺度残差块,其可以扩大感受野,更容易获得图像的全局信息。引入简易注意力模块,帮助网络更加关注图像复杂的部分,减少简单部分的比特。判别器部分采用全新的相对平均判别器,在网络框架中使用LPIPS(learned perceptual image patch similarity)感知损失减轻图像伪影问题。采用两阶段训练的方式解决引入生成对抗网络导致训练不稳定的问题。实验结果表明了在低码率下所提模型的有效性,与之前的工作相比,所提方法在感知失真指标上表现更优,性能提升了65%左右,重建图像更符合人类视觉感知。