基于码率-准确率优化的图像特征压缩

在智慧城市、智慧巡检、智慧交通等场景中,摄像头等终端设备会产生大量的图像视频数据,并在云端由智能处理算法进行图形分析。然而传统的源端图像视频压缩传输,后端特征提取与分析识别的处理框架易造成视觉特征受损,影响分析识别精度。因此,源端提取图像特征,压缩后传输到后端的处理框架成为新的热点。文中提出了一种基于码率-准确率优化的图像特征压缩方法。首先,提取图像特征,分析划分特征图重要性的标准,将特征图分为重要性和非重要性特征两部分,并分别进行量化。在此基础上,建立码率-准确率的模型,在给定码率条件下,求解最优的准确率,确定相应的量化参数。以图像分类作为智能分析任务开展了实验。实验结果表明,所提出方法可以优化选择不同区域的量化参数,获得更好的编码性能。在低码率的条件下,相较JPEG算法准确率提高9.73%。

数字电视发射机的调制技术与误码率优化研究

本文主要研究数字电视发射机的调制技术及误码率优化方法。在调制技术方面,首先介绍了调制技术的基本概念,然后列举了常见的数字电视调制技术,并对它们进行了比较和选择。在误码率优化方面,首先定义了误码率,然后探讨了影响误码率的因素。最后,通过调制参数优化、信道编码技术优化和信号处理技术优化等方法,提出了数字电视发射机调制技术的误码率优化方法。该研究对数字电视发射技术的发展和性能提升具有重要意义。

DTMB发射机LDPC编码器的设计与优化

介绍了中国数字电视地面传输标准中基于累加移位寄存器(SRAA)结构的低密度奇偶校验码(LDPC)编码的硬件实现方法和资源占用情况。并在此基础上,提出了提高硬件存储资源利用率的单码率优化及三码率整合方案。

基于光纤通信的电视信号高质量传输技术研究

光纤通信技术因其高带宽、低损耗和抗干扰能力被广泛应用于电视信号的高质量传输中。研究聚焦于基于光纤通信的电视信号传输技术,围绕信号的高效调制、损耗补偿以及传输系统优化展开。文章提出以波分复用技术为核心的多通道传输方案,结合高速光信号处理技术来实现信号在长距离传输中的稳定性和高保真。对传输过程中信号损耗与色散问题使用色散补偿光纤和光放大器优化传输链路性能,同时对信号放大和再生技术进行参数调优以进一步降低误码率。系统设计层面结合信号压缩和编码优化策略,有效提升了信号的传输效率与质量。结果表明基于优化的光纤通信系统可以改善电视信号的传输性能,为未来超高清信号传输及大容量多媒体应用提供了可行性参考。

基于允许绝对误差指标的静态图像编码算法

提出了一种新的静态图像编码方法,通过将小波域编码和误差的图像域编码相结合,并进行码率优化,使得在满足绝对误差要求的前提下减少总输出码率。同时提出了一种等效误差编码算法,该算法减少了编码的比特平面数,从而进一步降低最终输出码率。

基于系统Raptor码不等差错保护的图像压缩传输

该文提出一种在无线信道上进行图像传输的方案。喷泉码具有码率无关性,无需反馈信道,降低了系统复杂度。然而,传统喷泉码存在译码效率低、信息恢复质量对噪声敏感的问题。该方案基于系统Raptor码,在信道条件理想的情况下无需译码,提高了译码效率;引入不等差错保护(UEP)特性,根据信息重要性进行码率优化,使系统在不同信道环境中具有更好的稳定性。实验结果表明,在二进制删除信道信道(BEC)下,与传统纠错码和LT码及采用等差错保护(EEP)的Raptor码相比,该方案可显著提高传输的可靠性,获得更好的图像恢复效果。

一种H.264帧内预测模式的快速选择算法

H.264/AVC视频编码标准采用码率—失真度最优化(RDO)算法,以保证更高的压缩效率和更好的图像质量,但同时也大大增加了编码器的复杂度和运算负担。本文提出了一种新型的帧内预测模式的快速选择算法,该算法基于图像内部信息的变化剧烈程度进行判断,并通过方向矢量来减少候选帧内预测模式。试验结果表明,该算法可以将整个编码时间减少到原来采用RDO算法时的40%～50%,而且和RDO算法比较,最终压缩后的视频图像质量基本没有下降。

Regenerative Strategy for Sum-rate Enhancement in Bi-directional Three-node Cooperation

In bi-directional three-node cooperation, one regenerative strategy with network coding and power optimization is proposed for system sum-rate under a total energy constraint. In this paper, the network coding and power optimization are applied to improve system sum-rate. But max-rain optimization problem in power allocation is a NP-hard problem. In high Signal-to-Noise Ratio regime, this NP-hard problem is transformed into constrained polynomial optimization problem, which can be computed in polynomial time. Although it is a suboptimal solution, numerical simulations show that this strategy enhances the system sum-rate up to 45% as compared to a traditional four-phase strategy, and up to 13% as compared to the three-phase strategy without power optimization.

Frame complexity optimized selection for H.264/AVC video coding

To improve the coding performance of H.264/AVC, this paper proposes a rate control scheme composed of a novel flame complexity optimized selection and a quantization parameter （QP） value computation approach. First, it extracts the frame coding complexity from two rate distortion models, and then introduces five statistic modes to estimate the frame coding complexity. An optimal mode is selected according to the coding efficiency. Finally the paper presents a novel QP calculation method for the H.264/AVC rate control. Experimental results show that the proposed algorithra outperforms the algorithm integrated in the 3M model in obtaining precise frame coding complexity, achieving robust buffer control and improving coding quality. And the improving visual quality is high up to 0.90dB for CIF sequences.

A Novel Algorithm of Solving the Optimal Slope on Rate-distortion Curve for the Given Rate Budget

Rate-distortion optimization greatly improves the performance of compression coding system so that it pervades all of the source coding from an informationtheoretic standpoint and for the design of practical coding systems. For the case of rate-distortion optimization, Lagrange multiplier method provides the efficient and nearly optimal solution. In this paper, a fast and efficient algorithm is proposed to solve the optimal slope λ＊ of the rate-distortion curve at the given bit budget. Based on Lagrange multiplier method, the presented algorithm find λ＊ using the golden-ratio search. Compared with the Bisection method that only adapts to the system with the dense operational points on the rate-distortion curve, the proposed algorithm can be adapted to the system whether the operational points are populated densely or not. Thus it can be applied to both the wavelet coding system and the video coding standards such as H. 264, where Bisection method can not work well. In particular, the algorithm has been verified on the platform of the quadtree classified and trellis coded quantized （QTCQ） wavelet image compression system and the newest video coding standard H. 264. The experimental results are provided to demonstrate the efficiency of the algorithm. The proposed algorithm can improve the performance. A gain abour 0.6 - 0.7 dB can be achieved with the same rate in H. 264. In addition, it converges as fast as Bisection method, with almost the same ctinplexity.

A Rate-distortion Based Quantization Level Adjustment Algorithm in Block-based Video Compression

In this paper, a rate-distortion based quantization level adjustment （RDQLA） algorithm is presented. Based on the rate-distortion criterion, the quantization level adjustment algorithm effectively improves coding efficiency by adaptively optimizing quantization levels of the signals near the boundaries of quantization cells and adjusting quantization levels per block. In addition, it has no overhead and is fully compatible with the existing compression standards. The proposed algorithm can be applied in any block based image and video coding method. In particular, the algorithm has been verified on the platform of H.264. Experimental results show that the proposed algorithm improves objective and subjective performances substantially. It is shown that the proposed algorithm has a gain of several dB comparing with the newest H.264 standard for high bit rates.