一個用於MPEG-4視訊壓縮編碼 之視訊物件分割法的評估準則

An Evaluation Criterion of Visual Object Segmentation Methods for MPEG-4 Video Compression

徐祥豐(Hsiang-Feng Hsu)

指導教授 ： 繆紹綱

中原大學/工學院/電子工程研究所/碩士(2003年)

https://doi.org/10.6840/cycu200300471

摘要

摘要

隨著MPEG4視訊編碼標準的發展，影像物件(video object)的觀念也愈來愈受重視。MPEG-4提供影像物件的壓縮標準，以及一個場景中影像物件的定義，即場景描述。而把一個影像序列中的每個影像物件分開來獨立做處理是MPEG-4重要的創新之一。由於MEPG並未對影像物件分割訂定標準，因此衍生出了許多的影像物件分割方法。
在眾多的影像分割方法中，並沒有一個適用於所有情況的的影像分割方法，也沒有一個通用的準則來評斷影像分割方法的好壞，大部分都是以其應用層面來選擇適合的影像分割方法。在本論文中，我們提出一個以熵(Entropy)為基礎之成本函數的評判準則來預估一個分割結果後之MPEG-4的編碼效益，而一影像序列的成本函數基本上等於當中各物件之形狀、動作及紋理之熵的權重和。
在實驗中，我們針對幾種不同影像分割方法(如Watershed與Mean-shift)分割後的視訊物件進行實驗。實驗結果顯示，由該成本函數所預測之編碼效應與實際編碼所得結果相對應，證實我們提出的評判準則能經由簡單的成本函數運算後可有效預估分割後視訊的編碼效益，進而得知何種分割方法對MPEG-4視訊編碼而言較佳。

關鍵字：MPEG-4、影像切割、影像壓縮、影像物件、熵、評估準則

關鍵字

影像壓縮 ； 影像切割 ； MPEG-4 ； 影像物件 ； 評估準則 ； 熵

並列摘要

Abstract

As the development of MPEG-4 video compression standard, the concept of video object becomes more important. MPEG-4 provides standardized ways to encode video objects, and the scene description, which indicates how the objects are organized in a scene. One of the most important innovations that MPEG-4 brings is the capability of manipulating the individual objects in an image sequence. However, in MPEG-4 the decomposition or spatial-temporal segmentation of a scene into objects is not standardized. Therefore, many object-based segmentation algorithms have been proposed in the literature recently.
These segmentation algorithms use different sets of techniques and result in different performance. Although many approaches try to evaluate image segmentation quantitatively, a universal algorithm for segmenting images and a general criterion for the evaluation of segmentation results do not exist, and most techniques are tailored to particular applications. In this thesis, we propose an entropy-based cost function, which is the weighting sum of each video object’s shape entropy, motion entropy, and texture entropy in a visual sequence to quantitatively predict the coding efficiency of MPEG-4 for a particular segmentation result.
In the experiment, we comparatively evaluate several different segmentation approaches (Watershed and Mean-shift methods, for example) for object-based video segmentation. Experiment results show that the expected results of using the cost function coincide with actual coding results. Therefore, we have verified that by this cost function, we can easily predict which segmentation algorithm can have better coding performance for MPEG-4 video compression.
keywords: MPEG-4, Image Segmentation, Image Compression, Video Object, Entropy, Evaluation Criterion

並列關鍵字

Image Compression ； MPEG-4 ； Image Segmentation ； Evaluation Criterion ； Entropy ； Video Object

參考文獻

[1] C. Stiller and J. Konrad, “Estimating motion in image sequences,” IEEE Signal Processing Magazine, Vol. 16, Iss. 4, pp. 70-91, July 1999.

[2] M. Kim, J. G. Choi, D. Kim, H. Lee, M. H. Lee, C. Ahn, and Y.-S. Ho, “A VOP generation tool: automatic segmentation of moving objects in image sequences based on spatio-temporal information,” IEEE Trans. Circuits and Systems for Video Technology, Vol. 9, Iss. 8, pp. 1216-1226, Dec. 1999.

[4] A. R. Weeks and G. E. Hague, “Color segmentation in the HSI color space using k-means algorithm,” Proc. of the SPIE - Nonlinear Image Processing VIII, San Joese, CA, pp. 143-154, Feb. 1997.

[5] D. Comaniciu and P. Meer, “Robust analysis of feature spaces color image segmentation,” Proc. of IEEE Conf. Computer Vision and Pattern Recognition, pp. 750-755, June 1997.

[6] W. Y. Ma and B. S. Manjunath, “Edge flow: A framework of boundary detection and image segmentation,” Proc. of IEEE Conf. Computer Vision and Pattern Recognition, pp. 744 –749, June 1997.