基于小波变换的序列图像感兴趣区域编码
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摘要
感兴趣区域(Region-of-interest,ROI)编码技术,即在图像中的感兴趣区域采用低压缩比的有损压缩,甚至无损压缩;而在非感兴趣(背景)区域,采用高压缩比的有损压缩,这样既能够获得较高的全图压缩比,又可以保持图像中的重要信息不丢失,为解决图像压缩比与重建图像质量之间的矛盾提供了一个新的思路,具有重要的理论意义和应用价值。
根据国内和国际上的相关研究,本文对序列图像ROI编码中的几项关键技术进行了探讨,主要包括ROI位平面偏移方法、序列图像的运动估计算法,以及对ROI的动态跟踪算法等,其目的是建立一种实用的序列图像ROI编码系统,为未来的遥感图像分析、远程医疗和视频通信等应用领域提供算法支持。
本文的创新性工作概括如下:
1、提出了一种通用的部分位平面偏移方法(Generalized Partial Bitplanes ShiftMethod,GPBShift)。与标准方法中将全部位平面用统一的偏移值进行移位不同,该方法将ROI系数和背景系数的位平面分别划分成两部分,进行不同的位平面偏移。GPBShift方法兼容Maxshift、GBbBShift和PSBShift三种方法,并提供比上述方法更大的灵活性。它不仅能够在不需要传输ROI形状信息的情况下,对任意形状的ROI进行编码,而且通过选择偏移值,可以灵活调整ROI和背景区的相对压缩质量。此外,它还能够根据不同的优先级,编码多个ROI区域。
2、提出了一种可预测搜索起点的自适应交叉—准菱形搜索算法(PredictiveAdaptive Cross-Quasi-Diamond Search Algorithm,PACQDSA)。根据序列图像中运动矢量的交叉—中心偏置分布特性和矢量间的时空相关性,该算法设计了一种交叉—准菱形搜索模板,并融合搜索起点预测、半途中止准则和自适应搜索模式等技术,在保证搜索精度的同时,大幅度提高了运动估计的速度,尤其对于大运动序列,具有更明显的优势。
3、提出了一种基于Hausdorff距离的ROI跟踪算法。该方法首先采用一种新型的非线性边缘检测算法提取ROI模板和待匹配图像帧的边缘特征点,接着用Hausdorff距离将ROI模板的二维二值模型与后续帧进行匹配,然后采用一种基于运动相连成分的模型刷新方法对模型的每一帧进行更新,最终利用二值模型从视频序列中提取出ROI。
4、提出了一种适于图像压缩的小波基选择和评估的新方法。通过分析小波基函数的数学特性,该方法提出用六个指标全面评估小波基的压缩性能。这六个指标包括:熵H、编码增益G、峰—峰比PPR和增益的乘积PPR×G、最低频子带重构图像的峰值信噪比PSNR、能量集中特性,以及能量分布特性。实验结果显示:该方法能够正确对小波基进行评估,并据此选择出适当的小波基。
Region-of-interest (ROI) image coding technique means to compress interestingregions in an image without loss or with little loss, and to compress uninteresting(background) regions with much loss. Based on this idea a high compression ratio canbe obtained and the important information can be preserved in the image. ROI codingtechnique provides a new way to solve the contradiction between the compressionratio and the image quality. Therefore, it is of great significance in theory andapplications.
Based on the correlative research at home and abroad, this dissertation discussedsome key techniques related to ROI coding of sequence image, which include ROIbitplanes shift method, motion estimation algorithm, ROI tracking algorithm, and soon. All the work of this dissertation is focused on the realization of ROI video codingsystem by software for such applications as remote sensing image analysis, remotediagnosis and video communication.
The major innovations achieved in the dissertation are as follows:
1. A new ROI coding method called generalized partial bitplanes shift (GPBShift)is presented. To control the relative importance between ROI and background, themethod divides the bitplanes of ROI and background coefficients into two parts byusing scaling values S1 and S2, respectively. Instead of shifting the bitplanes all atonce by the same scaling value S in the standard methods, GPBShift shifts part ofthem on the basis of the bitplane shifting scheme. The Maxshift, generalizedbitplane-by-bitplane shift (GBbBShift) and partial significant bitplanes shift(PSBShift) methods are special cases of the GPBShift method, while GPBShiftprovides more flexibility for “degree-of-interest” adjustment of the ROI. TheGPBShift method not only is able to code arbitrarily shaped ROI without explicitlytransmitting any shape information to the decoder, but also flexibly select the scalingvalues to adjust relative compression quality in ROI and background. Additionally,the method may efficiently code multiple ROI with different priorities in an image.
2. A predictive adaptive cross-quasi-diamond search algorithm (PACQDSA) ispresented. Based on the cross-center-biased motion vector distribution characteristicof the real-world sequences and high space-time correlation of adjacent blocks'motion vectors, a new cross-quasi-diamond search pattern is designed with sucheffective techniques as prediction of initial search point, half-stop criteria and
adaptive search modes. Experiments show that the algorithm is able to fit all types ofvideo sequences adaptively in spite of the degree of the motions. And it is better thanthe traditional fast motion estimation algorithms such as NTSS, FSS and DS, in termsof both speed and PSNR, especially for the sequences with large motion.3. An ROI tracking algorithm based on Hausdorff distance is presented. Thealgorithm detects edge pixels in an ROI model and an image frame as the recognitionfeatures, then using them matches the ROI in subsequent frames by using theHausdorff distance rule. The ROI model is updated in real time using a new methodbased on the concept of the moving connected components. Finally, the ROIs areextracted from the binary model sequence.4. A new method for selection and evaluation of wavelet bases in imagecompression is proposed. By analyzing mathematical characteristics of wavelet base,several criteria are presented which include entropy, coding gain, product ofpeak-to-peak ratio (PPR) and coding gain, PSNR of the reconstructed image, energycollection characteristic and energy distribution characteristic. The experimentalresults show that the method is effective on selection and evaluation of wavelet bases.
根据国内和国际上的相关研究,本文对序列图像ROI编码中的几项关键技术进行了探讨,主要包括ROI位平面偏移方法、序列图像的运动估计算法,以及对ROI的动态跟踪算法等,其目的是建立一种实用的序列图像ROI编码系统,为未来的遥感图像分析、远程医疗和视频通信等应用领域提供算法支持。
本文的创新性工作概括如下:
1、提出了一种通用的部分位平面偏移方法(Generalized Partial Bitplanes ShiftMethod,GPBShift)。与标准方法中将全部位平面用统一的偏移值进行移位不同,该方法将ROI系数和背景系数的位平面分别划分成两部分,进行不同的位平面偏移。GPBShift方法兼容Maxshift、GBbBShift和PSBShift三种方法,并提供比上述方法更大的灵活性。它不仅能够在不需要传输ROI形状信息的情况下,对任意形状的ROI进行编码,而且通过选择偏移值,可以灵活调整ROI和背景区的相对压缩质量。此外,它还能够根据不同的优先级,编码多个ROI区域。
2、提出了一种可预测搜索起点的自适应交叉—准菱形搜索算法(PredictiveAdaptive Cross-Quasi-Diamond Search Algorithm,PACQDSA)。根据序列图像中运动矢量的交叉—中心偏置分布特性和矢量间的时空相关性,该算法设计了一种交叉—准菱形搜索模板,并融合搜索起点预测、半途中止准则和自适应搜索模式等技术,在保证搜索精度的同时,大幅度提高了运动估计的速度,尤其对于大运动序列,具有更明显的优势。
3、提出了一种基于Hausdorff距离的ROI跟踪算法。该方法首先采用一种新型的非线性边缘检测算法提取ROI模板和待匹配图像帧的边缘特征点,接着用Hausdorff距离将ROI模板的二维二值模型与后续帧进行匹配,然后采用一种基于运动相连成分的模型刷新方法对模型的每一帧进行更新,最终利用二值模型从视频序列中提取出ROI。
4、提出了一种适于图像压缩的小波基选择和评估的新方法。通过分析小波基函数的数学特性,该方法提出用六个指标全面评估小波基的压缩性能。这六个指标包括:熵H、编码增益G、峰—峰比PPR和增益的乘积PPR×G、最低频子带重构图像的峰值信噪比PSNR、能量集中特性,以及能量分布特性。实验结果显示:该方法能够正确对小波基进行评估,并据此选择出适当的小波基。
Region-of-interest (ROI) image coding technique means to compress interestingregions in an image without loss or with little loss, and to compress uninteresting(background) regions with much loss. Based on this idea a high compression ratio canbe obtained and the important information can be preserved in the image. ROI codingtechnique provides a new way to solve the contradiction between the compressionratio and the image quality. Therefore, it is of great significance in theory andapplications.
Based on the correlative research at home and abroad, this dissertation discussedsome key techniques related to ROI coding of sequence image, which include ROIbitplanes shift method, motion estimation algorithm, ROI tracking algorithm, and soon. All the work of this dissertation is focused on the realization of ROI video codingsystem by software for such applications as remote sensing image analysis, remotediagnosis and video communication.
The major innovations achieved in the dissertation are as follows:
1. A new ROI coding method called generalized partial bitplanes shift (GPBShift)is presented. To control the relative importance between ROI and background, themethod divides the bitplanes of ROI and background coefficients into two parts byusing scaling values S1 and S2, respectively. Instead of shifting the bitplanes all atonce by the same scaling value S in the standard methods, GPBShift shifts part ofthem on the basis of the bitplane shifting scheme. The Maxshift, generalizedbitplane-by-bitplane shift (GBbBShift) and partial significant bitplanes shift(PSBShift) methods are special cases of the GPBShift method, while GPBShiftprovides more flexibility for “degree-of-interest” adjustment of the ROI. TheGPBShift method not only is able to code arbitrarily shaped ROI without explicitlytransmitting any shape information to the decoder, but also flexibly select the scalingvalues to adjust relative compression quality in ROI and background. Additionally,the method may efficiently code multiple ROI with different priorities in an image.
2. A predictive adaptive cross-quasi-diamond search algorithm (PACQDSA) ispresented. Based on the cross-center-biased motion vector distribution characteristicof the real-world sequences and high space-time correlation of adjacent blocks'motion vectors, a new cross-quasi-diamond search pattern is designed with sucheffective techniques as prediction of initial search point, half-stop criteria and
adaptive search modes. Experiments show that the algorithm is able to fit all types ofvideo sequences adaptively in spite of the degree of the motions. And it is better thanthe traditional fast motion estimation algorithms such as NTSS, FSS and DS, in termsof both speed and PSNR, especially for the sequences with large motion.3. An ROI tracking algorithm based on Hausdorff distance is presented. Thealgorithm detects edge pixels in an ROI model and an image frame as the recognitionfeatures, then using them matches the ROI in subsequent frames by using theHausdorff distance rule. The ROI model is updated in real time using a new methodbased on the concept of the moving connected components. Finally, the ROIs areextracted from the binary model sequence.4. A new method for selection and evaluation of wavelet bases in imagecompression is proposed. By analyzing mathematical characteristics of wavelet base,several criteria are presented which include entropy, coding gain, product ofpeak-to-peak ratio (PPR) and coding gain, PSNR of the reconstructed image, energycollection characteristic and energy distribution characteristic. The experimentalresults show that the method is effective on selection and evaluation of wavelet bases.
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