近年來多媒體通訊廣泛地應用影像壓縮的技術以減少儲存的資訊量和網路傳輸的負
載。大部分的壓縮演算法會先把影像切割成大小相同的方塊，再對每個方塊進行離散餘
弦轉換，並且分別量化每個方塊離散餘弦轉換後的係數。然而這種方法卻會在還原影像
的方塊邊緣上造成明顯可見的方塊效應。有鑑於此，本論文提出一個高效能的演算法，
可以偵測出方塊的大小和方塊邊界的位置，並有效地去除方塊效應。此演算法毋需得知
壓縮的參數及標準，只須利用影像中的部分資料分批進行運算，故非常適合硬體實作。
經實驗結果證明，此演算法對於不同的測試影像，皆較其他演算法有穩定及精準的表現。

In order to reduce the storage and transmission costs, image compression has been widely
used in multimedia communication. Most compression methods employ block-based DCT
transform and quantize the DCT coefficients independently. However, it leads to visible
artifacts along block boundaries in the decompressed image. In this thesis, we propose an
algorithm to detect the block size and block boundary position of the decompressed image,
and remove the blocking artifacts by directional filter and low-pass filter. Our algorithm can
applied to various compression specifications without knowing any compression parameters.
Moreover, the segment-based procedure of our algorithm is extremely suitable for hardware
implementation. The simulation results show that our algorithm can effectively detect the
block size and block boundary position among different test images and has the more
outstanding performance in comparison with three existing methods.

Contents
Contents............................................................................................ i
List of Figures ................................................................................ iii
List of Tables ................................................................................... v
Chapter1 Introduction ................................................................... 1
Chapter2 Blocking Artifacts and Existing Deblocking Methods 3
2.1 Blocking Artifacts ................................................................................................... 3
2.2 Existing Deblocking Methods................................................................................. 4
2.2.1 Deblocking of Block-Transform Compressed Images Using Weighted
Sums of Symmetrically Aligned Pixels ................................................................ 5
2.2.2 Low complexity deblocking method for DCT coded video signals........... 13
Chapter3 Proposed Algorithm .................................................... 21
3.1 Detection of Block Size and Block Boundary Position ........................................ 21
3.2 Deblocking ............................................................................................................ 31
Chapter4 Experiment Results ..................................................... 37
4.1 The Results of Block Size and Block Boundary Detection .................................. 37
4.2 The Results of Deblocking.................................................................................... 49
ii
Chapter5 Conclusions and Future work .................................... 58
5.1 Conclusions ........................................................................................................... 58
5.2 Future Work .......................................................................................................... 59
References ..................................................................................... 60
Biography...................................................................................... 62

References
[1] Amir Z. Averbuch, Alon Schclar, and David L. Donoho. Deblocking of block-transform
compressed images using weighted sums of symmetrically aligned pixels. IEEE
Transactions on Image Processing, 14(2):200-212, February 2005.
[2] Roberto Castagno, Stefano Marsi and Giovanni Ramponi. A simple algorithm for the
reduction of blocking artifacts in images and its implementation. IEEE Transactions on
Consumer Electronics, 44(3):1062-1070, August 1998.
[3] Tao Chen, Hong Ren Wu, and Bin Qiu. Adaptive postfiltering of transform coefficients
for the reduction of blocking artifacts. IEEE Transactions on Circuits and Systems for
Video Technology, 11(5):594-602, May 2001.
[4] Yuh-Feng Hsu and Yung-Chang Chen. A new adaptive separable median filter for
removing blocking effects. IEEE Transactions on Consumer Electronics, 39(3):510-513,
August 1993.
[5] Byeungwoo Jeon, and Jechang Jeong. Blocking artifacts reduction in image compression
with block boundary discontinuity criterion. IEEE Transactions on Circuits and Systems
for Video Technology, 8(3):345-357, June 1998.
[6] Sung Deuk Kim, Jaeyoun Yi, Hyun Mun Kim, and Jong Beom Ra. A deblocking filter
with two separate modes in block-based video coding. IEEE Transactions on Circuits and
Systems for Video Technology, 9(1):156-160, February 1999.
[7] Y. L. Lee, H. C. Kim, and H. W. Park. Blocking effect reduction of JPEG images by
61
signal adaptive filtering. IEEE Transactions on Image Processing, 7(2):229-234,
February 1998.
[8] Alan W.-C. Liew, and Hong Yan. Blocking Artifacts suppression in block-coded images
using overcomplete wavelet representation. IEEE Transactions on Circuits and Systems
for Video Technology, 14(4):450-461, April 2004.
[9] Ying Luo and Rabab K. Ward. Removing the blocking artifacts of block-based DCT
compressed images. IEEE Transactions on Image Processing, 12(7):838-842, July 2003.
[10] S.-C. Tai, Y.-R. Chen, C.-Y. Chen and Y.-H. Chen. Low complexity deblocking method
for DCT coded video signals. IEE Proceedings - Vision, Image and Signal processing,
153(1):46-56, February 2006.
[11] Shen-Chuan Tai, Yen-Yu Chen, and Shin-Feng Sheu. Deblocking filter for low bit rate
MPEG-4 video. IEEE Transactions on Circuits and Systems for Video Technology,
15(6):733-741, June 2005.
[12] Ci Wang, Wen-Jun Zhang, and Xiang-Zhong Fang. Adaptive reduction of blocking
artifacts in DCT domain for highly compressed images. IEEE Transactions on Consumer
Electronics, 50(2):647-654, May 2004.
[13] Zhou Wang, Alan C. Bovik, and Brian L. Evans. Blind measurement of blocking artifacts
in images. 2000. Proceedings. 2000 International Conference on Image Processing,
3:981-984, 2000.
[14] Y. Zhao, G. Cheng and S. Yu. Postprocessing technique for blocking artifacts reduction
in DCT domain. Electronics Letters, 40(19):1175-1176, September 2004