International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volu...
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volu...
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volu...
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volu...
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volu...
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volu...
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Comparison of ezw and h.264 2

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Comparison of ezw and h.264 2

  1. 1. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 3, May – June (2013), © IAEME291COMPARISON OF EZW AND H.264Sangeeta Mishra, Sudhir SawarkarResearch Scholar, Amravati, DMCE, AiroliABSTRACTMotion compensation techniques are an important part of almost all video codecssince they provide an effective way of exploiting the temporal redundancy between frames inan image sequence. EZW (Embedded Zerotrees of Wavelet Transforms) is a lossy imagecompression algorithm. At low bit rates (i.e. high compression ratios) most of the coefficientsproduced by a subband transform (such as the wavelet transform) will be zero, or very closeto zero. This occurs because "real world" images tend to contain mostly low frequencyinformation (highly correlated). H.264/MPEG-4 Part 10 or AVC (Advanced Video Coding)is a standard for video compression. This paper mainly presents a comparison of two mainvideo compression techniques first using Embedded Zerotree Wavelet (EZW) algorithm &second using H.264 Codec.Index Terms—Motion estimation,AVC, video compression, MPEG, H.264,EZW.1. INTRODUCTIONReducing the transmission bit-rate while concomitantly retaining image quality is themost daunting challenge to overcome in the area of very low bit-rate video coding, e.g.,H.26X standards. The MPEG-4 [2] video standard introduced the concept of content-basedcoding, by dividing video frames into separate segments comprising a background and one ormore moving objects. This idea has been exploited in several low bit-rate macroblock-basedvideo coding algorithms [3] using a simplified segmentation process which avoids handlingarbitrary shaped objects, and therefore can employ popular macroblock-based motionestimation techniques. Such algorithms focus on moving regions through the use of regularpattern templates, from a pattern codebook, of non-overlapping rectangular blocks of 16×16pixels, called macroblocks (MB).INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING& TECHNOLOGY (IJCET)ISSN 0976 – 6367(Print)ISSN 0976 – 6375(Online)Volume 4, Issue 3, May-June (2013), pp. 291-296© IAEME: www.iaeme.com/ijcet.aspJournal Impact Factor (2013): 6.1302 (Calculated by GISI)www.jifactor.comIJCET© I A E M E
  2. 2. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 3, May – June (2013), © IAEME2922. VIDEO COMPRESSIONWith the advent of the multimedia age and the spread of Internet, video storage onCD/DVD and streaming video has been gaining a lot of popularity. The ISO Moving PictureExperts Group (MPEG) video coding standards pertain towards compressed video storage onphysical media like CD/DVD, where as the International Telecommunications Union (ITU)addresses real-time point-to-point or multi-point communications over a network. The formerhas the advantage of having higher bandwidth for data transmission. In either standard thebasic flow of the entire compression decompression process is largely the same and isdepicted in Fig.1 shows the block diagram for video compression process. The mostcomputationally expensive part in the compression process is the Motion Estimation. MotionEstimation examines the movement of objects in sequence to try to obtain the vectorsrepresenting the estimated motion. Encoder side estimates the motion of the current framewith respect to previous frame. A motion compensated image of the current frame is thencreated. Motion vector is then transmitted to decoder. Decoder reverses the whole processand creates a full frame. This way motion compensation uses the knowledge of object motionto achieve data compFig.1: Block Diagram for Video Compression process flow.The encoding side estimates the motion in the current frame with respect to a previousframe. A motion compensated image for the current frame is then created that is built ofblocks of image from the previous frame. The motion vectors for blocks used for motionestimation are transmitted, as well as the difference of the compensated image with thecurrent frame is also EZW encoded and sent. The encoded image that is sent is then decodedat the encoder and used as a reference frame for the subsequent frames. The decoder reversesthe process and creates a full frame. The whole idea behind motion estimation based videocompression is to save on bits by sending EZW encoded difference images which inherentlyhave less energy and can be highly compressed as compared to sending a full frame that isEZW encoded.3. EZWThe embedded zerotree wavelet algorithm (EZW) is a simple, yet remarkablyeffective, image compression algorithm, having the property that the bits in the bit stream are
  3. 3. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 3, May – June (2013), © IAEME293generated in order of importance, yielding a fully embedded code. The embedded coderepresents a sequence of binary decisions that distinguish an image from the “null” image. J.M. Shapiro proposed EZW image coding method in 1992. It has lead to a new generation ofpowerful wavelet image coders that exploit the dependency between wavelet coefficients inscale and space. Zerotree coding reduces the cost of encoding the significance map byexploiting the interscale dependency of wavelet coefficients [1]. Using an embedded codingalgorithm, an encoder can terminate the encoding at any point thereby allowing a target rateor target distortion metric to be met exactly. Also, given a bit stream, the decoder can ceasedecoding at any point in the bit stream and still produce exactly the same image that wouldhave been encoded at the bit rate corresponding to the truncated bit stream. In addition toproducing a fully embedded bit stream, EZW consistently produces compression results thatare competitive with virtually all known compression algorithms on standard test images.This performance is achieved with a technique that requires absolutely no training, no pre-stored tables or codebooks, and requires no prior knowledge of the image source.Fig.2 EZW flowchart to encode of DWT coefficients4. H.264 CODECThe intent of the H.264/AVC project was to create a standard capable of providinggood video quality at substantially lower bit rates than previous standards (i.e., half or less thebit rate of MPEG-2, H.263, or MPEG-4 Part 2), without increasing the complexity of designso much that it would be impractical or excessively expensive to implement. An additionalgoal was to provide enough flexibility to allow the standard to be applied to a wide variety ofapplications on a wide variety of networks and systems, including low and high bit rates, lowand high resolution video, broadcast, DVD storage, RTP/IP packet networks, and ITU-Tmultimedia telephony systems[4][5].A general block diagram is shown in fig.3. In this diagram the input video is supplied.Then video goes to next block which processes video based on EZW algorithm and H.264codec .After processing the original video compressed video is regenerated.
  4. 4. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 3, May – June (2013), © IAEME294Fig 3: Data Flow Diagram5. RESULTS AND DISCUSSIONWe have implemented embedded zerotree wavelet algorithm (EZW) and H.264 codecon different videos. We have calculated MSE, PSNR, Compression ratio & Compressionfactor for four different videos.We have done the comparison of all the parameters listed above on different videos.We have got compression ratios for different videos as 60% to 70%, compression ratioobtained by EZW is lesser then the H.264 codec.Demonstration of frames generated of “vipconcentricity.avi”:a)Frames of “vipconcentricity.avi”1. Original Frames:2. Reconstructed Frames by EZW:3. Frames Generated by H.264:
  5. 5. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 3, May – June (2013), © IAEME295Frames of “casio.avi”1. Original Frames2. Reconstructed Frames by EZW:3. Frames Generated by H.264:Table 1 below shows the comparison of different parameters between EZW and H.264 onfour different videos from the MATLAB demos.Table1. Comparison of EZW & H.264
  6. 6. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 3, May – June (2013), © IAEME2966. FUTURE SCOPEWe have seen that intra prediction and motion compensation are just two parts of thewhole decoder of H.264. In the decoder, there are still other parts such as deblockingfiltering, entropy decoding (CAVLC or CABAC), and inverse transform (IDCT). Theseprocessing units can be employed to accelerate the processing speed and reduce thecomputation load of the microprocessor. For a complete H.264 decoding system, theseprocessing units and a microprocessor have to be integrated into the system. Then appropriatedesigns of interface and data communication become important issues when integrating thewhole system from the top view.The EZW algorithm achieves excellent compression performance, usually higher than that ofarithmetic coding and Huffman coding. Algorithm offers additional advantages such asspatial random access and ease of geometric manipulation.7. REFERENCES1. J. M. Shapiro, “Embedded image coding using zero trees of wavelet coefficients”,IEEE Trans. Signal Processing, vol.41, pp. 3445-3462, 1993.2. Mohammed Ghanbari :Video Coding And Introduction To Standard Codecs .3. I.Richardson: Video Coding for Next Generation Multimedia.4. G. J. Sullivan, P. Topiwala, and A. Luthra, "The H.264/AVC Advanced VideoCoding Standard: Overview and Introduction to the Fidelity Range Extensions",Presented at the SPIE Conference on Applications of Digital Image ProcessingXXVII Special Session on Advances in the New Emerging Standard: H.264/AVC,August 2004.5. Thomas Wiegand, Gary J. Sullivan, “Overview of the H.264/AVC Video CodingStandard”, IEEE transactions on circuits and systems for videotechnology,vol.13,no.7,July 2003.6. Dhaval R. Bhojani and Dr. Ved Vyas Dwivedi, “Novel Idea for Improving VideoCodecs”, International Journal of Electronics and Communication Engineering&Technology (IJECET), Volume 4, Issue 2, 2013, pp. 301 - 307, ISSN Print:0976- 6464, ISSN Online: 0976 –6472.7. Pardeep Singh, Nivedita and Sugandha Sharma, “A Comparative Study: BlockTruncation Coding, Wavelet, Embedded Zerotree and Fractal Image Compression onColor Image”, International Journal of Electronics and Communication Engineering& Technology (IJECET), Volume 3, Issue 2, 2012, pp. 10 - 21, ISSN Print:0976- 6464, ISSN Online: 0976 –6472.

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