论文（设计）-一种改进的基于小波去噪和区域生长的彩色图像分割算法21374.doc

专业好文档一种改进的基于小波去噪和区域生长的彩色图像分割算法刘肖，李宏，葛立敏（西北工业大学, 西安, 710072）摘要：彩色图像分割是彩色图像处理中的重要问题，传统的彩色图像分割都是基于灰度分割算法，而忽略了彩色的空间域视觉效果及噪声污染问题。本文提出一种新的基于小波去噪和种子区域生长的一种改进方法。首先，应用小波去噪技术，强化图像边缘特征，抑制噪声，提高原始图像的信噪比；其次，将彩色图像转化到空间进行边缘检测，对图像进行抖动处理以减少彩色图像中的颜色数目，然后对不同分量进行序列阀值分割；最后对分割结果再进行一种新的基于区域生长的颜色相似性的聚合。仿真结果表明该算法更加符合人眼的视觉特性。关键词：彩色图像；彩色空间；小波去噪；区域生长中图分类号： TP391 文献标识码：AAn improved color image segmentation algorithm based on waveletdenoising and regional growthLIU Xiao, LI Hong, GE Li Min(School of electronics and information in Northwestern Polytechnical University, Xi'an 710072,China )Abstract: Color image segmentation is an important issue in color image processing. The traditional color image segmentation based on gray-scale segmentation algorithms neglects the color visual effect and the noise, it, therefore, leads to degrade the segmentation quality. In this paper, we present a new algorithm based on wavelet denoising and seed regional growth. The denoising technique is first used to preserve the edge feature of the original image. Then, the images incolor space are converted intocolor space. Next, a jitter processing is used to reduce the number of colors in color image segmentation, and then the images are segmented in terms of sequence threshold on the different components. Finally, color similarity polymerization, based on regional growth, is applied to the processed image. The simulation results show that the segmentation results obtained by our method have perfect edge segmentation, and correspond well with the vision properties of the human being.Key words: color image; color space; wavelet denoising；regional growth1引言图像分割是由图像处理进行到图像分析的关键步骤,也是进一步图像理解的基础。以往所研究的算法大多是针对灰度图像的,相比之下对于彩色图像分割的研究较少.基于颜色空间特性的方法一般采取区域分割和聚类的方法来实现，但区域分割的结果很大程度上依赖于种子点的选择，常常会造成图像过分割或者欠分割的问题。Horowitz首次将分裂合并思想用于图像分割，但由于算法的局限性难以实现小区域的有效连接。聚类方法中比较常见的是K-mean聚类和模糊c聚类法，然而在这类方法中，聚类的数目需预先设定，每次迭代优化都需要重新计算聚类中心和隶属度矩阵，计算量较大。近年来，有学者提出利用边缘生长的技术进行图像分割，先对图像进行边缘检测，然后用有向势能函数对边缘进行粗略的封闭，最后用区域生长的技术进行细分割，该方法虽然可以有效解决漏分割的问题，但分割结果不够光滑，存在一定的误差。本文充分利用彩色图像的颜色空间特性，结合图像中区域之间的特征相似性关系，提出一种改进的基于区域生长的新算法。该方法首先对图像进行小波去噪处理以抑制噪声，然后将颜色空间转换到与人类视觉特性相符的颜色空间，并按分量序列依次进行分割，最后进行基于颜色相似性聚类的区域生长。因为区域生长算法可以利用同一个目标区域其邻域块特征基本一致的特点, 对整幅图像的子块扫描一遍就可完成分割, 不需反复迭代。从而该算法可实现对彩色图像的快速准确分割。2.算法描述针对传统算法的缺陷，本文提出以下改进方案，如下图所示： 图1 算法流程图2.1小波去噪近年来，小波理论得到了非常迅速的发展。在信号去噪领域中，由于其具有良好的时频特性，同样取得了较好的效果。相比于其它传统的去噪方法，小波去噪能够很好的强化边缘特征。其基本思想如下：首先对原始图像进行小波分解得到小波系数，然后选择阀值，对所得到的小波系数进行修正，最后用修正的小波系数，重构图像。本文采用的小波系数修正方法是广泛采用的Donoho和Johostone提出的小波萎缩方法(VisulShrink)，其阀值定义为，为噪声的方差，为图像的像素个数，可以用小波系数的中位值估计。计算出后，我们采用软阀值法调整，调整方法如下：(1)然后用修改后的重构图像，去除噪声。2.2彩色空间图像处理中常用的颜色模型多数为颜色模型和颜色模型。对任何3个0,1范围内的、值，可以用如下的计算公式得到其对应模型中的、分量： （2） 在空间中，、三分量之间的相关性比、三分量之间要小的多。由于彩色空间的表示比较接近人眼的视觉生理特性，人眼对、变化的区分能力要比对、变化的区分能力强。另外在空间中彩色图像的每一个均匀性彩色区域都对应一个相对一致的色调，这说明色调能够被用来进行独立于阴影的彩色区域的分割。2.3 区域生长传统的种子区域生长法选择图像中部分象素点作为种子，然后将与种子性质相似的相邻象素附加到生长区域的每个种子上。本文我们根据一定规则自动选取部分区域作为种子区域，克服了种子点区域选取的盲目性，然后将与种子区域性质相似的相邻区域附加到种子所在区域去。种子区域的选择在该算法中起到了至关重要的作用，而对于种子区域的选取我们将遵循一定的规则。要求种子区域在其相邻区域中有一定的代表性，使生长的结果更接近我们期望的区域。进行种子区域选取的规则如下：规则1：种子区域与其领域有很高的相似性。这里我们为每个区域定义一个相似度函数。一个区域的相似度函数必须大于一个阀值，我们用二维大津法确定阀值，该区域才能被选为种子区域。一个区域与其领域的相似度函数定义为： （3） （4）为中每个区域的色调分量均值。为集合所有区域的色调分量均值。 （5）为中每个区域的饱和度分量均值，为中集合所有区域的饱和度分量均值。为预先设定值，经验上一般选择。规则2：一个区域与它的相邻区域的相对欧式距离的最大值要小于一个阀值。这里采用欧式距离的定义对区域的色调分量均值进行计算，公式如下： （6）其中为的相邻区域个数，规则2可以保证选出的种子区域的位置不处在期望的两个区域的边界处，该阀值的选取依经验我们选择0.2。在一个未标记的区域将加入到一个种子区域之前，先将它们的同一性差值与一个阀值做比较，如果低于这个阀值，则进行标记，否则不被标记。然后将种子区域进行合并。2.4 空间变换我们可以将颜色空间变换运用于图像分割中，当彩色图像的分割在空间进行时，由于、三个分量是相互独立的，所以有可能将这个3D搜索问题转化为三个1D搜索。：1 对原始彩色图像进行空间转换和边缘检测，对梯度较大的轮廓边缘进行标记，利用分量来区分高饱和区和低饱和区；2 利用分量对高饱和区进行分割：由于在高饱和彩色区值大，值量化细，可采用色调的阀值来进行分割；3 利用对低饱和区进行分割：在低饱和彩色区量化粗无法直接用来分割，但由于比较接近灰度区域，因而可采用来进行分割；4 由于彩色图像象素过大，为了加快算法速度，对H值进行归一化处理，即令；3 仿真实现下面对一幅原始彩色图像Lena.tif在matlab7.1环境下进行分割，为了增强效果，将本算法结果与传统的梯度法进行比较。先对其进行小波去噪及抖动处理，避免噪声影响。图(b)为噪声污染后的图像,信噪比为30dB，图(c)为传统梯度法结合小波去噪的分割结果，图(d)和图(e)分别取迭代次数为130和150时的仿真结果。 图2 算法仿真结果一个好的分割结果一般希望轮廓线比较平滑，形状测度就是提出来衡量目标外轮廓的光滑程度的。如以表示象素的领域中的平均灰度，表示象素处的梯度，C是一个归一化系数 为设定的某一阀值：则 （6）下表为仿真数据： 表1.仿真结果分析由上表可以看出，本文算法的形状测度值明显低于传统算法，即分割结果的光滑性较好，成功融合了区域和色彩信息，在视觉效果方面优于传统算法。并且对指定区域细节的分割更加准确，这无疑会为图像分割的后继处理，图像识别，图像检索打下更好的基础。上述彩色图像分割算法简便快速适合于对实时性要求高的场合，如用于电视会议的分析合成编码方法中作为自动的图像分割算法以将诸如人脸等区域从图中分割出来分别编码。4结论本文提出的新算法是基于空间的序列分割方法，将小波去噪引入彩色空间处理彩色图像，并且在色度空间变换的基础上引入了基于颜色聚类的区域生长法，本文的方法用区域代替像素作为种子进行生长，从算法时间复杂度的角度来说算法效率有较大提高；另一方面，由于区域所携带的信息远高于像素所携带的信息，更有利于之后的区域生长，因而能取得更好的分割效果。我们使用 MATLAB 实现了我们的算法，实验结果证明，我们的算法在彩色图像分割上，取得了较好的效果。仿真结果表明该算法可以清晰地分割彩色图像，可以看出来分割效果较好，符合人的主观感知，与人类视觉系统判断基本一致，可以满足一般基于内容的图像检索或识别处理。参考文献1 章毓晋.图像分割M.北京：科学出版社,2001.97-1232唐挺等.基于小波去噪和图像分割技术的改进NAS-RIF盲图像复原算法J.成都信息工程学院学报.2004.19(3).3 罗军辉等.Matlab7.0在图像处理中的应用M.北京：机械工业出版社，2005.64 王佳男.采用基于区域的自动种子区域生长法的彩色图像分割方法D.东北师范大学硕士论文.2007.55 罗希平，田捷等. 图像分割方法综述J. 模式识别与人工智能.1999. 12(3): 300-312.6 H D Cheng, X H Jiang, Y Sun & J Wang. Color image segmentation: advances and prospects J. PatternRecognition. 2001.34(9): 2259-2281.作者简介刘肖(1984-),女,汉族,硕士，研究方向:图像处理,模式识别等。李宏(1958-),男,汉族,教授,研究方向:MIMO系统的空时编码和信道的自适应估计。葛立敏(1984-),男,汉族,硕士,研究方向：机载合成孔径雷达成像方向的研究。联系方式：西安市友谊西路127西北工业大学35信箱邮编：710072电话：029-88486133, 13572533820Email：lx.1021163.comEditor's note: Judson Jones is a meteorologist, journalist and photographer. He has freelanced with CNN for four years, covering severe weather from tornadoes to typhoons. Follow him on Twitter: jnjonesjr (CNN) - I will always wonder what it was like to huddle around a shortwave radio and through the crackling static from space hear the faint beeps of the world's first satellite - Sputnik. I also missed watching Neil Armstrong step foot on the moon and the first space shuttle take off for the stars. Those events were way before my time.As a kid, I was fascinated with what goes on in the sky, and when NASA pulled the plug on the shuttle program I was heartbroken. Yet the privatized space race has renewed my childhood dreams to reach for the stars.As a meteorologist, I've still seen many important weather and space events, but right now, if you were sitting next to me, you'd hear my foot tapping rapidly under my desk. I'm anxious for the next one: a space capsule hanging from a crane in the New Mexico desert.It's like the set for a George Lucas movie floating to the edge of space.You and I will have the chance to watch a man take a leap into an unimaginable free fall from the edge of space - live.The (lack of) air up there Watch man jump from 96,000 feet Tuesday, I sat at work glued to the live stream of the Red Bull Stratos Mission. I watched the balloons positioned at different altitudes in the sky to test the winds, knowing that if they would just line up in a vertical straight line "we" would be go for launch.I feel this mission was created for me because I am also a journalist and a photographer, but above all I live for taking a leap of faith - the feeling of pushing the envelope into uncharted territory.The guy who is going to do this, Felix Baumgartner, must have that same feeling, at a level I will never reach. However, it did not stop me from feeling his pain when a gust of swirling wind kicked up and twisted the partially filled balloon that would take him to the upper end of our atmosphere. As soon as the 40-acre balloon, with skin no thicker than a dry cleaning bag, scraped the ground I knew it was over.How claustrophobia almost grounded supersonic skydiverWith each twist, you could see the wrinkles of disappointment on the face of the current record holder and "capcom" (capsule communications), Col. Joe Kittinger. He hung his head low in mission control as he told Baumgartner the disappointing news: Mission aborted.The supersonic descent could happen as early as Sunday.The weather plays an important role in this mission. Starting at the ground, conditions have to be very calm - winds less than 2 mph, with no precipitation or humidity and limited cloud cover. The balloon, with capsule attached, will move through the lower level of the atmosphere (the troposphere) where our day-to-day weather lives. It will climb higher than the tip of Mount Everest (5.5 miles/8.85 kilometers), drifting even higher than the cruising altitude of commercial airliners (5.6 miles/9.17 kilometers) and into the stratosphere. As he crosses the boundary layer (called the tropopause), he can expect a lot of turbulence.The balloon will slowly drift to the edge of space at 120,000 feet (22.7 miles/36.53 kilometers). Here, "Fearless Felix" will unclip. He will roll back the door.Then, I would assume, he will slowly step out onto something resembling an Olympic diving platform.Below, the Earth becomes the concrete bottom of a swimming pool that he wants to land on, but not too hard. Still, he'll be traveling fast, so despite the distance, it will not be like diving into the deep end of a pool. It will be like he is diving into the shallow end.Skydiver preps for the big jumpWhen he jumps, he is expected to reach the speed of sound - 690 mph (1,110 kph) - in less than 40 seconds. Like hitting the top of the water, he will begin to slow as he approaches the more dense air closer to Earth. But this will not be enough to stop him completely.If he goes too fast or spins out of control, he has a stabilization parachute that can be deployed to slow him down. His team hopes it's not needed. Instead, he plans to deploy his 270-square-foot (25-square-meter) main chute at an altitude of around 5,000 feet (1,524 meters).In order to deploy this chute successfully, he will have to slow to 172 mph (277 kph). He will have a reserve parachute that will open automatically if he loses consciousness at mach speeds.Even if everything goes as planned, it won't. Baumgartner still will free fall at a speed that would cause you and me to pass out, and no parachute is guaranteed to work higher than 25,000 feet (7,620 meters).It might not be the moon, but Kittinger free fell from 102,800 feet in 1960 - at the dawn of an infamous space race that captured the hearts of many. Baumgartner will attempt to break that record, a feat that boggles the mind. This is one of those monumental moments I will always remember, because there is no way I'd miss this.