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题名:
基于匹配跟踪的低速率视频编码
作者: 廖斌
答辩日期: 2003
专业: 计算机应用技术
授予单位: 中国科学院软件研究所
授予地点: 中国科学院软件研究所
学位: 博士
关键词: 小波变换 ; 匹配跟踪 ; 视频图像编码 ; 视觉保真 ; 感兴趣区域 ; 位分配
其他题名: Low-bit Rate Video and Image Coding Based on Matching Pursuit
摘要: 目前,针对低速率信道(10kb/s~60kb/s)如无线通道和电话线上的视频通讯的应用需求越来越广泛。虽然已经制定的一些国际视频编码标准,如H.261、H.263、MPEG-1和MPEG-2,在各种商业应用中获得很大成功,但是在窄带条件下往往会产生人眼敏感的方块效应和图像抖动现象,损害了恢复视频的视觉质量,因此尚不能够满足在极低速率(低于20kb/s)下的应用。而在静态图像编码方面,虽然小波图像算法的编码性能远远超过第一代图像压缩标准JPEG,但它在低位率条件下也会出现蚊式噪音,主要集中在图像边缘附近,而且对于包含丰富纹理的自然图像,其编码效率也会急剧下降。为了提高低速率编码效率,本文综合小波变换以及匹配跟踪非线性信号分解技术,并结合人类视觉系统HVS的各种特性,致力于提高视频编码算法在低速率条件下的编码性能,并对所涉及到的若干问题进行了探索和解决,并取得如下创新性研究成果:1.分析了小波系数图像统计特性,并指出零树编码方案EzW在处理孤立零点以及边缘纹理上存在的问题,在此基础上提出双零树根结构和基于高阶统计建模的自适应算术编码的方案,进一步减少子带内残存的统计冗余。实验分析结果表明,该方案具有较好的图象压缩效果。2.建立基于小波变换十匹配跟踪技术的低位率图像编码方案。它将图像划分为一组包含不同信号特征的图像层,如低频边缘层和纹理层等等,对于前者可以选择采用小波零树编码方案,而对后者则采用基于冗余字典的匹配分解算法。利用这种编码思想,可以充分考虑不同变换方法的特性,将它们最优的组合在一起,完成对一幅图像各种特征的有效编码。最后的实验数据表明,该算法在低位率条件下的编码性能明显超过单纯的小波图像编码算法。3.建立一个基于匹配跟踪信号分解技术的低速率视频编码器框架。基本思想是对于预测误差图像信号的分解,不再采用传统的晶格DCT变换,而是选择采用一个拥有更多基函数的冗余字典集合。而且,通过选择非晶格结构的字典(原子函数之间允许重叠),从根本上避免了低速率DCT系统带来的方块边缘失真,增加估计的精度,减少对运动信息编码耗费并提高在低速率下的视觉效果。4.建立一个基于视觉保真的匹配跟踪视频编码方案。在这一部分,我们将人类视觉特性引入到匹配跟踪编码器的位分配过程中,试图提高恢复图像的主观视觉效果。在低速率编码条件下,由于总的允许分配比特数量有限,通过调整位分配过程,可以使得某些人眼感兴趣的区域的图像恢复质量高于其它区域。最后,对全文进行总结,分析目前研究工作中有待完善的地方,同时指明进一步研究的方向。
英文摘要: Currently, the demands of video communication on low bit-rate channels (10kb/s~60kb/s), such as wireless channel and telephone network, are becoming more and more comprehensive. Although some existed international video coding standards, such as H.261, H.263, MPEG-1 and MPEG-2, has wined great success in all kinds of commercial applications. But for all these standards, the phenomena of sensible blocking artifacts or image dithering will emerge under narrow bands, which impair the visual quality of reconstructed images. So, these standards still couldn't satiate the demands of very low bit-rate applications (under 20kb/s). As to still image coding, even though the performance of wavelet image coding algorithms excel first generation image compression standard JPEG, but they will produce boring mosquito noise at low bit-rates, which are mainly located around image edges. Besides that, their coding efficiency will drop rapidly for those natural images with rich textures. In order to improve coding efficiency at low bit-rates, this thesis adopted wavelet and nonlinear matching pursuit techniques, combined with some characteristics of human visual system, aimed at improve the performance of video coding at low bit-rates. The major contributions of this thesis are included in the following: On a basis of the analysis of statistical properties of wavelet image, the problems existed in EZW are pointed out. At the same time, the deficits of zerotree coding will be discussed. Then, we give our modification of zerotree structure, and propose adaptive image coding based on high order statistical modeling, which aims at removing statistical redundancy existed in subbands. The results of experiments proved our scheme has better image compression quality. A new low bit-rate image-coding algorithm based on wavelet and matching pursuit is proposed. Such method divides the whole image into a series of image layers including different signal characteristics, such as low-freq&edge layer and texture layer. For the first, we adopt wavelet image algorithm; For the latter, matching pursuit based on redundant dictionary is utilized. In such way, we can consider the advantages of different transform methods and combine them together to code the image in an optimal way. Last experiments showed the performance of the proposed method outgoes the single wavelet image algorithm. A low bit-rate video-coding scheme based on matching pursuit is built in this section. The main idea lies in decomposing the difference frame of prediction in a redundant dictionary with much more basis functions, giving up traditional lattice DCT transform. By choosing non-hybrid dictionary, blocking artifacts of DCT system can be avoided ultimately. The cost of coding motion information is reduced, so the visual quality of images at low bit-rates is improved. Building a matching pursuit video coder based on visual fidelity. In this section, the characteristics of human visual system are introduced into bit allocation of coder, in order to improve subject visual quality of reconstructed images. At low bit-rates, because of limitation of the budget bits, we can make the quality of regions absorbing eye focus higher than other regions by adjusting bit-allocation. Finally, the key points of the thesis are concluded, some improvements to be done in the current research are analyzed, and some suggestions and expectations for future work are provided.
语种: 中文
内容类型: 学位论文
URI标识: http://ir.iscas.ac.cn/handle/311060/7402
Appears in Collections:中科院软件所

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Recommended Citation:
廖斌. 基于匹配跟踪的低速率视频编码[D]. 中国科学院软件研究所. 中国科学院软件研究所. 2003-01-01.
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