CN100466746C - 基于宏块内边缘信息选择分割的方法 - Google Patents

基于宏块内边缘信息选择分割的方法 Download PDF

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CN100466746C
CN100466746C CNB2005100441293A CN200510044129A CN100466746C CN 100466746 C CN100466746 C CN 100466746C CN B2005100441293 A CNB2005100441293 A CN B2005100441293A CN 200510044129 A CN200510044129 A CN 200510044129A CN 100466746 C CN100466746 C CN 100466746C
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CN1901679A (zh
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田树民
王晓慧
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Hisense Group Co Ltd
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Hisense Group Co Ltd
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    • H04W88/00Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
    • H04W88/02Terminal devices
    • H04W88/06Terminal devices adapted for operation in multiple networks or having at least two operational modes, e.g. multi-mode terminals
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W88/00Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
    • H04W88/08Access point devices
    • H04W88/085Access point devices with remote components
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W88/00Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
    • H04W88/16Gateway arrangements
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W92/00Interfaces specially adapted for wireless communication networks
    • H04W92/04Interfaces between hierarchically different network devices
    • H04W92/12Interfaces between hierarchically different network devices between access points and access point controllers
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02DCLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00Reducing energy consumption in communication networks
    • Y02D30/70Reducing energy consumption in communication networks in wireless communication networks
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S370/00Multiplex communications
    • Y10S370/901Wide area network
    • Y10S370/902Packet switching
    • Y10S370/903Osi compliant network
    • Y10S370/906Fiber data distribution interface, FDDI
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S370/00Multiplex communications
    • Y10S370/901Wide area network
    • Y10S370/902Packet switching
    • Y10S370/903Osi compliant network
    • Y10S370/907Synchronous optical network, SONET

Abstract

本发明所述基于宏块内边缘信息选择分割的方法,针对帧间图像的运动预测,利用人眼对物体边缘信息比较敏感这一特性,提出一种针对物体边缘信息的快速确定宏块的分割方法,可以有效提高运算速度、降低复杂程度。其步骤是,第一步,进行针对宏块的预分割。根据宏块中是否含有边缘信息来划分。通过预分割得到的含有边缘信息的块,继续下步处理。第二步,将可再分割的、即含有边缘信息的块,进行试探性运动估计。包括边缘像素点预判,对于像素残差绝对值之和SAD不小于预设阈值的块进行下一级的分割。若不能再分割,将确定为最终分割子块;若还可分割,对此块再进行试探性运动估计,重复上面的步骤,直至完成整个宏块的分割。

Description

基于宏块内边缘信息选择分割的方法
技术领域
本发明是一种应用于视频编解码的宏块分割方法,具体的是在运动估计中基于内边缘信息进行快速分割。
背景技术
目前电子行业中的视频编解码标准,如ITU的H.261,H.263,H.264及MPEG组织的MPEG-1,MPEG-2,MPEG-4等标准都是采取以宏块为单位。所谓的宏块就是任意一帧图像被分成的具有一定容量的像素块。对于这些宏块,又可进一步地分割成若干个子块。
目前在数字视频压缩技术中,最常用的运动估计技术和运动补偿是基于块的方法。现有的算法多是针对16×16的宏块或其子块根据某种匹配准则和搜索算法在参考区域内进行匹配运算,以找到最佳匹配块并获得运动向量和像素残差值。如附图1所示的是一种比较常用的针对亮度宏块的7类分割块,最小的分块为4×4。越小的分块越能保证良好的显示精度,但相应地也需较大的运算量。
选择何种适合的宏块分割方法,不仅直接影响到整个解码的运算速度,同时也一定程度上决定了解码后的视频质量。现有选择宏块分割的方法,是对同一宏块运用多种分割方式,直至比较优选出最佳的分割方法。这类现有分割方法的运算速度较慢,且未基于当前帧图像的特点。另外,其他一些方法虽针对了物体运动等特征,但同时还是有着较高的算法复杂度。
发明内容
本发明所述基于宏块内边缘信息选择分割的方法,其目的在于解决上述问题和不足而针对帧间图像的运动预测,利用人眼对物体边缘信息比较敏感这一特性,提出一种针对物体边缘信息的快速确定宏块的分割方法,可以有效提高运算速度、降低复杂程度。
所述基于宏块内边缘信息选择分割的方法,所应用的宏块包括有16×16,8×16,16×8,8×8,8×4,4×8,4×4,这7种类型的子块。
所述选择分割方法的步骤如下,即:
第一步,进行针对宏块的预分割。
所述的预分割,是根据宏块中是否含有边缘信息来划分。预分割得到的不含有边缘信息的块,即4×4,4×8,8×4这三类块,将不再继续进行分割,确立为最终分割子块。
通过预分割得到的含有边缘信息的块,继续下步处理。
第二步,将可再分割的、即含有边缘信息的块,即16×16,8×16,16×8,8×8这四类块,进行试探性运动估计。
包括边缘像素点预判,对于像素残差绝对值之和SAD不小于预设阈值的块进行下一级的分割。
若不能再分割,将确定为最终分割子块;若还可分割,对此块再进行试探性运动估计,重复上面的步骤,直至完成整个宏块的分割。
上述方法第一步中所述的预分割,分为以下的步骤进行:
(1)、将宏块进行试探性运动估计,对于像素残差绝对值之和SAD与预设阈值t进行比较,将小于阈值t的宏块确定为不需进一步划分的宏块。
(2)、对于不满足上一步骤条件的宏块做边缘信息提取。
按照边缘信息的分布情况,以确定是做0级、1级还是2级的分割。其中,0级为该宏块不含有边缘信息,1级为宏块从中间均分后的任意一边含有边缘信息,2级为宏块从中间均分后的两边均含有边缘信息。
上述预分割处理的目的,在于将边缘信息较多的部分和边缘信息较少的部分进行分离,以便将含有边缘信息较多的块再继续进行分割。
实际上,边缘信息的分布情况由含有边缘信息的像素点的个数决定。所预设阈值t,对含有边缘像素点较少的块判定为非边缘信息块,将不再做进一步的分割。
将含边缘信息较多的块进行下一步分割。若分割成的两块都含有边缘信息,则停止分割;后续分割和所列出的分割方式的原理和方法都相同,一直到把宏块中有边缘信息和无边缘信息的部分全部分开,完成整个宏块的预分割,以划分所有边缘信息块和非边缘信息块。
进行预分割突出了边缘块的处理,淡化了非边缘块的处理。因为人眼更会注意细节信息,预分割只是针对边缘信息进行,且并没有进行搜索匹配,边缘信息的计算并不十分复杂,所以预分割部分的运算量并不是很大,速度是比较快的。
应用上述边缘信息提取的算法目前有多种选择,比如sobel算子,roberts算子,拉普拉斯,prewitt算子、小波变换等。
本发明的目的在于提高运算速度,因而对于算法优先选择prewitt算子和sobel算子。
上述方法第二步中对于边缘信息块的试探性运动估计,其步骤是:
确定块中含边缘信息像素点的位置和个数,提取参考块中同位置像素点,求这些像素值的残差绝对值之和SAD1,与预设阈值T1比较。
若能证明此参考块含有当前块边缘信息,再对整个块求SAD,再与预设阈值T2比较,如果参考块不含有当前块边缘信息将舍弃此参考块,并对下一块进行搜索匹配。
根据边缘信息预判的方法,不仅能更好的反映边缘信息,且在搜索的过程中减少了运算,能够加快整个运动估计的速度。
对于SAD和SAD1阈值的确定都是以单个残差值阈值与像素个数乘积确定的,所以对于子块的大小是自适应的,对于边缘块判定的阈值也是根据块的大小不同来规定的。
综上所述,基于宏块内边缘信息选择分割的方法针对MPEG-2,H264等视频标准中基于块的运动估计比较费时的特点,结合人眼对物体边缘比较敏感的特点,针对物体边缘信息的快速确定宏块的分割方式,能够有效地减少整个视频编码的时间,解码后的图像视觉效果较佳,同时该方法也可被应用到多参考帧的场合。
附图说明
图1是常见的宏块被分成7种子块的示意图。
图2是由宏块生成各类子块的示意图。
图3是应用priwitt算子模板提取边缘信息的示意图。
具体实施方式
实施例1,如图1至图3所示,应用所述基于宏块内边缘信息选择分割的方法,针对一帧图像确定其中所有宏块的分割方式的步骤是:
(1)、对当前帧划分成16×16的像素块(宏块)。
(2)、按从左到右,从上到下的顺序完成对所有宏块进行分割,先取第一个在参考帧中做试探性运动估计,对于像素残差绝对值之和SAD小于一个规定的阈值t1的,则此宏块采用0级分割,确立0级为该宏块的最终分割方式,记下此宏块位置。
(3)、若不是上一步骤(2)中的宏块,则对此宏块做边缘信息提取。
边缘提取采用prewitt算子,统计边缘像素点个数及位置,若小于阈值t2,进行0级分割;否则采用1级分割中的任一方式,分别对两部分中的边缘像素个数进行统计,若有其中一部分小于t2的二分之一,则确立为非边缘子块,并按此方式进行分割;
若两子块都为边缘子块,进行1级中另一方式分割,同样进行阈值检测,若找出非边缘子块,按此进行上述第(1)步的分割方式。
若不能得到非边缘子块,则第(1)步的分割确立为2级分割。同时,检测是否能找出非边缘子块。
记下第(1)步分割后的所有非边缘子块的位置,将这些子块确立为最终分割子块。
对于第(1)步分割后的边缘子块,再按图2进行下一步分割,若不能找到非边缘块。
则对此子块维持上一步的分割,若找到非边缘块,进行此种分割,记下非边缘块的位置并确定为子块最终分割方式。
按图2对非边缘块继续分割,直到不能再分割或完成所有分割为止,至此完成预分割。
(4)、对于所有预分割后的即含有边缘信息的块,即16×16,8×16,16×8,8×8这四类块,按像素进行预判运动估计和试探运动估计。
对于SAD不能达到要求(小于像素个数与单像素残差阈值乘积)的块再做下一步的分割。
分割后若属于4×8,8×4,4×4的块,则认定为确定此分割。
否则,再做预判运动估值和试探运动估值,达到要求的记下此块位置,确立为最终分割子块。
按以上四步完成所有宏块的分割。

Claims (4)

1、一种基于宏块内边缘信息选择分割的方法,其特征在于:所述方法的实现步骤是,
第一步,进行针对宏块的预分割,将不含有边缘信息的宏块和含有边缘信息的宏块加以区分;
对于不含有边缘信息的宏块,不再继续进行分割;
对于含有边缘信息的宏块,进行试探性运动估计;不能进行0级分割的宏块,进行边缘提取,将含有边缘信息的部分和不含边缘信息的部分以子块形式区分开,以完成预分割;
第二步,对于预分割后的含有边缘信息的边缘子块,在参考块内针对是否含有相同的边缘点进行预判,对于像素残差绝对值之和SAD不小于预设阈值的边缘子块进行下一级的分割;
若不能再分割,将确定为最终分割子块;
若还可分割,对预分割后的含有边缘信息的边缘子块再进行试探性运动估计;
重复第一步及第二步,直至完成整个宏块的分割。
2、根据权利要求1所述的基于宏块内边缘信息选择分割的方法,其特征在于:所述预分割的实现步骤是,
将宏块进行试探性运动估计,对于像素残差绝对值之和SAD与预设阈值进行比较,将小于阈值的宏块确定为不需进一步划分的宏块;
对于不满足上一步骤条件的宏块做边缘信息提取;
按照边缘信息的分布情况,以确定是做0级、1级还是2级的分割;
将含边缘信息较多的宏块进行下一步分割;若分割成的两块都含有边缘信息,则停止分割;后续分割和所列出的分割方式的原理和方法都相同,一直到把宏块中有边缘信息和无边缘信息的部分全部分开,完成整个宏块的预分割,以划分所有边缘信息块和非边缘信息块,含边缘信息较多的块即为含有边缘信息的像素点个数大于预设阈值的块。
3、根据权利要求1或2所述的基于宏块内边缘信息选择分割的方法,其特征在于:对于边缘信息块的试探性运动估计的步骤是,
确定块中含边缘信息像素点的位置和个数,提取参考块中同位置像素点,求这些像素值的残差绝对值之和SAD1,与预设阈值T1比较;
若能证明此参考块含有当前块边缘信息,再对整个块求SAD,再与预设阈值T2比较,如果参考块不含有当前块边缘信息将舍弃此参考块,并对下一块进行搜索匹配。
4、根据权利要求3所述的基于宏块内边缘信息选择分割的方法,其特征在于:按如下方式证明参考块含有当前块边缘信息:在参考块和当前块的边缘像素点位置取像素残差之和,根据像素残差之和做预判,预判通过再对整个块做匹配检测;
对于边缘信息块判定的阈值是根据块的不同大小来设定的。
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