基于率失真优化的嵌套式静态图像编码算法研究
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摘要
随着Internet的广泛应用，给传统的图像压缩和传输方式带来了巨大的挑战，而较好的解决方法之一就是利用嵌套式的静态图像编码所具有的渐进传输特性。在严格的带限信道中，能够及早的以低分辨率生成图像对用户来说是非常重要的，用户可以基于内容选择终止图像的传输或者是继续接收细节更精细的图像。
Internet网络中，用户具有不同的网络带宽和屏幕分辨率，因此图像编码必须适合广泛的可视环境，码流可在不同的情况下被解码和观看。理想情况下，在编解码的任意点裁减所得的不同码率的位流均是优化的，而不是单独优化每一个；另外一种情况下，编码速度足够快，可以针对用户的需要优化不同码率下的码流，但是裁减所得的码流有可能不是最优的。这两种情况都暗示了编码位流是嵌套式的，本文针对每一种情况都进行了详细的讨论。在接入低带宽信道时，具有低分辨率显示的计算机可以在码流开始生成图像，而不需接收太多的位生成高分辨率的图像。用户在高分辨率显示和高带宽接人网络时可以观看从同一码流解码生成的粗分辨率图像。
图像编码的率失真理论讨论了在给定允许失真条件下，所能达到的最大编码率。在给定的编码率下，可由率失真算法计算图像编码所能达到的最大的编码失真减小。先编码的位具有较大的信息量，反映了图像的轮廓，后编码的位反映了图像的细节。因此率失真理论对图像的嵌套式编码具有非常重要的理论指导意义。
嵌入式静态图像压缩编码近来引起了极大的关注，并且已经成为图像压缩算法的热点之一。本论文详细讨论了算法的基本原理及影响编码质量的各种因素，介绍了目前国内外所使用的主要的嵌套式编解码技术。在此基础上，本论文系统、深入地研究了小波域基于率失真优化的嵌套式静态图像编码方法。作者认为，以下问题制约算法的实际应用：
■ 编解码速度快，可以在实时的环境中应用。
■ 编码效果好，可以在任意码率下恢复出较圩质量的图像。
■ 嵌套式位流可以在任意点被裁减，编码器不但在最终码率是优化的，在每一个裁减点也是优化的。
■ 优化的子带位率分配和量化器步长能使得编码的均方误差值最小。
在分析嵌套式静态图像编码的基础上，本文对率失真优化的编码顺序和子带优化的位率分配与量化器步长进行了深入地研究，做出的主要贡献如下：
■ 本文提出了一种基于率失真斜率优化编码顺序的嵌套式静态图像编码算法。基于率失真斜率最陡的编码顺序所得的码流在任意点都是优化的。高码率的码流在任意点被截短后所得到的低码率码流与直接在该低码率编码所得的码流完全一样。仿真结果表明，该算法编码速度很快，算法实现非常简单，编码效果比较好。
.本文详细分析了基于Lagrange乘数的率失真优化理论，提出了一种标量量
化的嵌套式图像编码算法。率失真优化的子带位率分配和量化步长在高率时
是Lagrange乘数的线性函数。如果高码率的码流被截短后，编码性能将会
变差。仿真结果表明，该算法编码速度较快，编码效果也较好。
.本文详细分析了通用网格编码量化(uTcQ)的特点，提出了一种基于率失
真优化的渐进传输的通用网格编码量化方法。算法模拟了真实的UTCQ率
失真特性曲线。仿真结果表明，该算法编码速度适中，编码效果非常好。但
是高码率的码流被截短后，编码性能同样会变差。
With the widespread use of Internet, it has taken several great technical challenges for image compression and transmission. One of better solutions is utilizing characteristic of progressive transmission of embedded still image coding. On severely bandwidth limited channel, it is necessary that images can be rendered with a low resolution as early as possible. The user has the option to terminate the transmission based on the image content or to continue receiving the finer details of the image.
In the Internet, users have many different bandwidths and screen resolutions, so image compression algorithms must be suitable for a wide variety of viewing environments and bitstream may be decoded and viewed under many different circumstances. Ideally, the bitsteams with different coding bit-rate that can be gotten by truncating bitsteams at any point of coding and decoding are all optimized , rather than separate optimized for each.The othei circumstances,the speed of coding is quickly enough,and the bitstreams with different bit-rate can be optimized by user's demand.But the bitstreams by trunctioa are not optimized.Both of the circumstances imply that the image coded bitsireams must be embedded,and every one will be dicussed in details in this paper. Connected to low bandwidth channel, the computers with low resolution displays can render an image early in the bitstream without receiving many bits that are only required for high resolution rendering. A user with a high resolution display and a high band
width connection to the network should then be able to view a coa-se resolution version of the image which improves as additional bits are read from ihe same bitstream.
Under the given distortion conditions, ;he image coding Rate-Distortion theories discuss the max coding bit-rate. Unde the given coding bit-rate,the max coding distortion decrease can be calculated v/ith Rate-Distortion algorithms.The first coding bits have more information and reflect the image outlines,the last coding bits reflect the image details.So the Rate-Distor :ion theory is very important for the embedded still image coding.
Embedded still image coding receives great attention recently and becomes one of hot topics in image coripression algorithm. This paper introduces the fundamental theory and kinds of factors that influence the coding quality in details, introduces the main techniques of embedded coding at home and abroad. Based on those introduces, this paper researches embedded still coding methods with Rate-Distortion Optimization .
The author thinks, the main obstacles of the development of embedded coding technique in Image Compression are:
The speed of encoding and decoding must be quickly enough to be applied in real-time applications.
The effect of encoding is so better that the algorithm can render images under
any coding bit-rate conditions.
Embedded bit streams can be arbitrarily truncated at any point; the coder is not only optimized at the final rate, but also optimized at every trunction point.
How can we decide the subband bit allocations and quantization step sizes so that the Mean Squared Errors are minimum?
Based on the analysis of the main obstacle of embedded still image coding, this paper focus on the coding order with Rate-Distortion Optimized, subband bit allocations and quantization step sizes. And the main contributions are shown below:
This paper presents a kind of embedded still image coding algorithm with coding order with Rate-Distortion Optimized.Based on the steepest Rate-Distortion slope coding order, the bitstream is optimized at arbitrary point. The low coding bit-rate bitstream gotten by truncating high bit-rate one is the same as the bitstream gotten by coding immediately with the coding low bit-rate. The result shows that the speed of algorithm is very quick, the realization is very simple and coding effect is better.
This paper analyzes the theory of Rate-Distortion Optimization based on Lagrange Multiplier in details, and presents a kind of Embedded still image co
Internet网络中，用户具有不同的网络带宽和屏幕分辨率，因此图像编码必须适合广泛的可视环境，码流可在不同的情况下被解码和观看。理想情况下，在编解码的任意点裁减所得的不同码率的位流均是优化的，而不是单独优化每一个；另外一种情况下，编码速度足够快，可以针对用户的需要优化不同码率下的码流，但是裁减所得的码流有可能不是最优的。这两种情况都暗示了编码位流是嵌套式的，本文针对每一种情况都进行了详细的讨论。在接入低带宽信道时，具有低分辨率显示的计算机可以在码流开始生成图像，而不需接收太多的位生成高分辨率的图像。用户在高分辨率显示和高带宽接人网络时可以观看从同一码流解码生成的粗分辨率图像。
图像编码的率失真理论讨论了在给定允许失真条件下，所能达到的最大编码率。在给定的编码率下，可由率失真算法计算图像编码所能达到的最大的编码失真减小。先编码的位具有较大的信息量，反映了图像的轮廓，后编码的位反映了图像的细节。因此率失真理论对图像的嵌套式编码具有非常重要的理论指导意义。
嵌入式静态图像压缩编码近来引起了极大的关注，并且已经成为图像压缩算法的热点之一。本论文详细讨论了算法的基本原理及影响编码质量的各种因素，介绍了目前国内外所使用的主要的嵌套式编解码技术。在此基础上，本论文系统、深入地研究了小波域基于率失真优化的嵌套式静态图像编码方法。作者认为，以下问题制约算法的实际应用：
■ 编解码速度快，可以在实时的环境中应用。
■ 编码效果好，可以在任意码率下恢复出较圩质量的图像。
■ 嵌套式位流可以在任意点被裁减，编码器不但在最终码率是优化的，在每一个裁减点也是优化的。
■ 优化的子带位率分配和量化器步长能使得编码的均方误差值最小。
在分析嵌套式静态图像编码的基础上，本文对率失真优化的编码顺序和子带优化的位率分配与量化器步长进行了深入地研究，做出的主要贡献如下：
■ 本文提出了一种基于率失真斜率优化编码顺序的嵌套式静态图像编码算法。基于率失真斜率最陡的编码顺序所得的码流在任意点都是优化的。高码率的码流在任意点被截短后所得到的低码率码流与直接在该低码率编码所得的码流完全一样。仿真结果表明，该算法编码速度很快，算法实现非常简单，编码效果比较好。
.本文详细分析了基于Lagrange乘数的率失真优化理论，提出了一种标量量
化的嵌套式图像编码算法。率失真优化的子带位率分配和量化步长在高率时
是Lagrange乘数的线性函数。如果高码率的码流被截短后，编码性能将会
变差。仿真结果表明，该算法编码速度较快，编码效果也较好。
.本文详细分析了通用网格编码量化(uTcQ)的特点，提出了一种基于率失
真优化的渐进传输的通用网格编码量化方法。算法模拟了真实的UTCQ率
失真特性曲线。仿真结果表明，该算法编码速度适中，编码效果非常好。但
是高码率的码流被截短后，编码性能同样会变差。
With the widespread use of Internet, it has taken several great technical challenges for image compression and transmission. One of better solutions is utilizing characteristic of progressive transmission of embedded still image coding. On severely bandwidth limited channel, it is necessary that images can be rendered with a low resolution as early as possible. The user has the option to terminate the transmission based on the image content or to continue receiving the finer details of the image.
In the Internet, users have many different bandwidths and screen resolutions, so image compression algorithms must be suitable for a wide variety of viewing environments and bitstream may be decoded and viewed under many different circumstances. Ideally, the bitsteams with different coding bit-rate that can be gotten by truncating bitsteams at any point of coding and decoding are all optimized , rather than separate optimized for each.The othei circumstances,the speed of coding is quickly enough,and the bitstreams with different bit-rate can be optimized by user's demand.But the bitstreams by trunctioa are not optimized.Both of the circumstances imply that the image coded bitsireams must be embedded,and every one will be dicussed in details in this paper. Connected to low bandwidth channel, the computers with low resolution displays can render an image early in the bitstream without receiving many bits that are only required for high resolution rendering. A user with a high resolution display and a high band
width connection to the network should then be able to view a coa-se resolution version of the image which improves as additional bits are read from ihe same bitstream.
Under the given distortion conditions, ;he image coding Rate-Distortion theories discuss the max coding bit-rate. Unde the given coding bit-rate,the max coding distortion decrease can be calculated v/ith Rate-Distortion algorithms.The first coding bits have more information and reflect the image outlines,the last coding bits reflect the image details.So the Rate-Distor :ion theory is very important for the embedded still image coding.
Embedded still image coding receives great attention recently and becomes one of hot topics in image coripression algorithm. This paper introduces the fundamental theory and kinds of factors that influence the coding quality in details, introduces the main techniques of embedded coding at home and abroad. Based on those introduces, this paper researches embedded still coding methods with Rate-Distortion Optimization .
The author thinks, the main obstacles of the development of embedded coding technique in Image Compression are:
The speed of encoding and decoding must be quickly enough to be applied in real-time applications.
The effect of encoding is so better that the algorithm can render images under
any coding bit-rate conditions.
Embedded bit streams can be arbitrarily truncated at any point; the coder is not only optimized at the final rate, but also optimized at every trunction point.
How can we decide the subband bit allocations and quantization step sizes so that the Mean Squared Errors are minimum?
Based on the analysis of the main obstacle of embedded still image coding, this paper focus on the coding order with Rate-Distortion Optimized, subband bit allocations and quantization step sizes. And the main contributions are shown below:
This paper presents a kind of embedded still image coding algorithm with coding order with Rate-Distortion Optimized.Based on the steepest Rate-Distortion slope coding order, the bitstream is optimized at arbitrary point. The low coding bit-rate bitstream gotten by truncating high bit-rate one is the same as the bitstream gotten by coding immediately with the coding low bit-rate. The result shows that the speed of algorithm is very quick, the realization is very simple and coding effect is better.
This paper analyzes the theory of Rate-Distortion Optimization based on Lagrange Multiplier in details, and presents a kind of Embedded still image co
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114．《基于人眼视觉特性加权的率失真优化编码算法》《信号处理》2002年第18卷第五期，468-472。
115．《基于率失真优化的静态图象编码算法》，《系统工程与电子技术》2003年第25卷第三期，343-346页
116．《渐进的UTCQ编码算法》，《电子科学与信息》已录用，即将刊出。
117．《基于率失真优化的UTCQ编码算法》，《信号处理》修改后即将录用。
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