COMPARATIVE STUDY OF MPEG-4 AND H.264 VIDEO COMPRESSION STANDARDS

Transcription

1 COMPARATIVE STUDY OF MPEG-4 AND H.264 VIDEO COMPRESSION STANDARDS #1 GOPAL KASAT P.G SCHOLAR #2 SUHAS JADHAV Professor #3 ZAMEER FAROOQUI Professor Department Of Electronics and Telecommunication Engineering Aditya Engineering College, Beed, Maharashtra. ABSTRACT We propose an improved saliency guided wavelet compression scheme for low-bitrate image/video coding applications. Important regions (faces in security camera feeds, vehicles in traffic surveillance) get degraded significantly at low bitrates by existing compression standards, such as JPEG/JPEG-2000/MPEG- 4, since these do not explicitly utilize any knowledge of which regions are salient. We design a compression algorithm which, given an image/video and a saliency value for each pixel, computes a corresponding saliency value in the wavelet transform domain. Our algorithm ensures wavelet coefficients representing salient regions have a high saliency value. The coefficients are transmitted in decreasing order of their saliency.this allows important regions in the image/video to have high fidelity even at very low bitrates. Further, our compression scheme can handle several salient regions with different relative importance. We compare the performance of our method with the JPEG/JPEG-2000 image standards and the MPEG-4 video standard through two experiments: face detection and vehicle tracking. We show improved detection rates and quality of reconstructed images/videos using our Saliency Based Compression (SBC) algorithm. I.INTRODUCTION Recently, the exponential growth in networking technologies and widespread use of video content based multimedia information over internet for mass communication through social networking; e-commerce, education, etc. have promoted the development of video coding to a great extent. Various video coding schemes have already been designed for seamless transmission of digital video data and for mass storage of digital information. The primary goal of a video coding standard is to achieve higher compression performance while maintaining high visual quality. A human eye is space-variant non-uniform resolution sampling system. Hence, foveation based video coding yields higher compression performance by varying the visual quality of video data across the space to match the non-uniform spatial sampling of a human eye. In the present doctoral research work, efforts are made to develop fast and efficient foveated video compression schemes that achieve higher compression performance as well as higher visual quality at a lower computational complexity. 1.1 Digital Video Digital video is a three-dimensional data of a dynamic visual scene, sampled spatially and temporally. A visual scene temporally sampled at any time instant is known as a frame. Page No:1275

2 Figure 1.1: Illustration of Spatio-temporal sampling of a video scene 1.2 Fundamentals of Video Compression Background In the modern world, the demand of video data has increased manifold due to massive internet application like social networking, e-governance, security and surveillance, video telephony. Hence, the network bandwidth has become a major bottleneck for efficient Figure 1.4: Typical video coding system transmission of these vast amount of video data in real-time even if the present technology offers quite large bandwidths. Most probably, this problem will continue for ever since the modern human civilization will demand more and more for video transmission applications in future. Therefore, a well designed and efficient video compression system is always required to reduce transmission bit-rate for video data content without degrading the visual quality significantly. In a heterogeneous network, where medium to low data rates are supported, transmission of video data is even a more challenging task. The data rates available within a network vary across the channels according to the characteristics of a network, i.e. the types of the transmission channel and the receiving data terminal as well as the network traffic congestion. Consequently, video data must be transmitted at a variety of bit-rates to have efficient transmission. Some efficient and adaptive video compression schemes are required to solve these issues [1]. A typical video coding system is shown in Figure 1.4. A video data generated at the source is encoded with low bit-rate by a video encoder. The compressed video data is either sent to storage devices or transmitted through a communication channel. At the receiving end, the compressed video data is decoded by a video decoder and reconstructed video frames are displayed to users. II.LITERATURE REVIEW A space-variant non-uniform resolution image can be generated by various foveation filtering schemes. The encoding of oblique featured video data is a challenging task. Different directional transform schemes are available in literature, which efficiently encode these oblique featured video data. Motion estimation is one of the very important tools of a hybrid video compression schemes. Various motion estimation schemes are present in literature to find out the best matched block in a reference frame and enhance the compression efficiency with minimum computation cost. In this chapter, some well-known, efficient, standard and benchmark schemes related to different tools of efficient foveated video compression schemes, are studied. The proposed schemes, developed and designed in this doctoral research work, are compared against these in subsequent chapters. Therefore, attempts are made here for a detailed and critical analysis of these schemes. The literature review is categorized Page No:1276

3 into three domains of the proposed foveated video compression schemes as shown in Figure 2.1. The detailed discussion of each category is given below. 2.1 Foveated Video Compression Recently, foveated video compression (FVC) schemes have gain major interest by many researchers in the field of video coding. Since FVC schemes exploit non-uniformity in the resolution of the retina by allocating more number of bits to visual fixation points and reducing resolution drastically away from the fixation points, it delivers perceptually high quality at greatly reduced bandwidths. There are several efficient foveated video processing schemes available in literature, for example, foveation filtering (local bandwidth reduction) [4], saliency detection based foveating [6] and wavelet based foveated compression [3]. In 1993, Silsbee et al. have introduced the image coding based on the properties of human visual system (HVS) [4]. The video is encoded by dividing the frame into a number of spatio-temporal patterns which are based on spatio-temporal properties of HVS. The adaptation of foveated processing to various video coding standards is demonstrated by [2]. Broadly, foveation method can be classified into three categories: 1. Geometry based foveation (GBF), 2. Filtering based foveation (FBF) and 3. multi-resolution based foveation (MBF). In GBF schemes, uniformly sampled image coordinates are transformed into spatial variant coordinates by log map transform, also known as foveation coordinate transform, which exploits the retina sampling geometry [5]. Figure 2.1: Categorisation of literature review Wallace et al. [5] and Kortum and Geisler [4] have shown geometric transformation of uniform sampled image to non-uniform space variant sampled image using super pixel. The super pixels are generated to match the retinal sampling distribution by grouping and averaging the uniform pixels. Lee and Bovik have shown that foveation is a coordinate transformation from cartesian coordinates to curvilinear coordinates and a local bandwidth is uniformly distributed over curvilinear coordinates for a foveated image [5]. 2.2 Directional Transforms The recent developments in video acquisition and display systems and exponential growth in transmission bandwidths have increased the demand of superior quality video contents in multimedia applications with resolutions ranging from pixels (QCIF) to pixels (UHD). With widespread adoption of emerging applications like video streaming, video surveillance, blue-ray disk video, etc. video compression has become an integral component of such multimedia applications. However, a video data in an uncompressed format demands a huge amount of storage space and transmission bandwidth. To Page No:1277

4 surpass these physical constraints, an efficient video compression scheme is always required. Various video coding methods have been developed in literature to accomplish video compression such as entropy coding [8], predictive coding [9], block transform coding [6], wavelet/sub-band coding [1]. Block transform coding is the one which is highly exploited in image and video coding by reducing the inherent spatial redundancies between neighbouring pixels. single, low-resolution, uncompressed stream. Even with constant advances in storage and transmission capacity, compression is likely to be an essential component of multimedia services for many years to come. III.VIDEO COMPRESSION 3.1 INTRODUCTION Network bitrates continue to increase (dramatically in the local area and somewhat less so in the wider area), high bitrate connections to the home are commonplace and the storage capacity of hard disks, flash memories and optical media is greater than ever before. With the price per transmitted or stored bit continually falling, it is perhaps not immediately obvious why video compression is necessary (and why there is such a significant effort to make it better). Video compression has two important benefits. First, it makes it possible to use digital video in transmission and storage environments that would not support uncompressed ( raw ) video. For example, current Internet throughput rates are insufficient to handle uncompressed video in real time (even at low frame rates and/or small frame size). A Digital Versatile Disk (DVD) can only store a few seconds of raw video at television-quality resolution and frame rate and so DVD-Video storage would not be practical without video and audio compression. Second, video compression enables more efficient use of transmission and storage resources. If a high bitrate transmission channel is available, then it is a more attractive proposition to send highresolution compressed video or multiple compressed video channels than to send a Figure 3.1 Video frame (showing examples of homogeneous regions) Figure 3.2 Video frame (low-pass filtered background) MPEG-4 AND H.264 Page No:1278

5 compression (video coding) is the process of compacting or condensing a digital video sequence into a smaller number of bits. Raw or uncompressed digital video typically requires a large bitrate (approximately 216 Mbits for 1 second of uncompressed TV-quality video, see Chapter 2) and compression is necessary for practical storage and transmission of digital video. Compression involves a complementary pair of systems, a compressor (encoder) and a decompressor (decoder). Figure 3.3 Video frame 2 By removing different types of redundancy (spatial, frequency and/or temporal) it is possible to compress the data significantly at the expense of a certain amount of information loss (distortion). Further compression can be achieved by encoding the processed data using an entropy coding scheme such as Huffman coding or Arithmetic coding. Image and video compression has been a very active field of research and development for over 20 years and many different systems and algorithms for compression and decompression have been proposed and developed. In order to encourage interworking, competition and increased choice, it has been necessary to define standard methods of compression encoding and decoding to allow products from different manufacturers to communicate effectively. This has led to the development of a number of key International Standards for image and video compression, including the JPEG, MPEG and H.26 series of standards. 4. VIDEO COMPRESSION STANDARDS The encoder converts the source data into a compressed form (occupying a reduced number of bits) prior to transmission or storage and the decoder converts the compressed form back into a representation of the original video data. The encoder/decoder pair is often described as a CODEC (encoder/ DECoder) (Figure 4.1). Data compression is achieved by removing redundancy, i.e. components that are not necessary for faithful reproduction of the data. Many types of data contain statistical redundancy and can be effectively compressed using lossless compression, so that the reconstructed data at the output of the decoder is a perfect copy of the original data. Unfortunately, lossless compression of image and video information gives only a moderate amount of compression. Figure 4.1 Encoder/decoder 4.1 INTRODUCTION Compression is the process of compacting data into a smaller number of bits. Video Page No:1279

6 a fidelity as possible. These two goals (compression efficiency and high quality) are usually conflicting, because a lower compressed bit rate typically produces reduced image quality at the decoder. Figure 4.2 Spatial and temporal correlation in a video sequence The best that can be achieved with current lossless image compression standards such as JPEG-LS [1] is a compression ratio of around 4 4 times. Lossy compression is necessary to achieve higher compression. In a lossy compression system, the decompressed data is not identical to the source data and much higher compression ratios can be achieved at the expense of a loss of visual quality. Lossy video compression systems are based on the principle of removing subjective redundancy, elements of the image or video sequence that can be removed without significantly affecting the viewer s perception of visual quality. 4.2 VIDEO CODEC A video CODEC (Figure 4.4) encodes a source image or video sequence into a compressed form and decodes this to produce a copy or approximation of the source sequence. If the decoded video sequence is identical to the original, then the coding process is lossless; if the decoded sequence differs from the original, the process is lossy. The CODEC represents the original video sequence by a model (an efficient coded representation that can be used to reconstruct an approximation of the video data). Ideally, the model should represent the sequence using as few bits as possible and with as high Figure 4.3 Video encoder block diagram 5.MPEG-4 AND H INTRODUCTION MPEG-4Visual and H.264 (also known as Advanced Video Coding) are standards for the coded representation of visual information. Each standard is a document that primarily defines two things, a coded representation (or syntax) that describes visual data in a compressed form and a method of decoding the syntax to reconstruct visual information. Each standard aims to ensure that compliant encoders and decoders can successfully interwork with each other, whilst allowing manufacturers the freedom to develop competitive and innovative products. The standards specifically do not define an encoder; rather, they define the output that an encoder should produce. A decoding method is defined in each standard but manufacturers are free to develop alternative decoders as long as they achieve the same result as the method in the standard. MPEG-4 Visual (Part 2 of the MPEG-4 group of standards) was developed by the Moving Picture Experts Group (MPEG), a working group of the International Organisation for Standardisation (ISO). This group of several hundred technical experts Page No:1280

7 (drawn from industry and research organisations) meet at 2 4 month intervals to develop the MPEG series of standards. MPEG-4 (a multi-part standard covering audio coding, systems issues and related aspects of audio/visual communication) was first conceived in 1994 and Part 2 was standardised in The H.264 standardisation effort was initiated by the Video Coding Experts Group (VCEG), a working group of the International Telecommunication Union (ITU-T) that operates in a similar way to MPEG and has been responsible for a series of visual telecommunication standards. The final stages of developing the H.264 standard have been carried out by the Joint Video Team, a collaborative effort of both VCEG and MPEG, making it possible to publish the final standard under the joint auspices of ISO/IEC (as MPEG-4 Part 10) and ITU-T (as Recommendation H.264) in MPEG-4 Visual and H.264 have related but significantly different visions. Both are concerned with compression of visual data but MPEG-4 Visual emphasises flexibility whilst H.264 s emphasis is on efficiency and reliability. MPEG-4 Visual provides a highly flexible toolkit of coding techniques and resources, making it possible to deal with a wide range of types of visual data including rectangular frames ( traditional video material), video objects (arbitrary-shaped regions of a visual scene), still images and hybrids of natural (real-world) and synthetic (computer-generated) visual information. MPEG-4 Visual provides its functionality through a set of coding tools, organised into profiles, recommended groupings of tools suitable for certain applications. Classes of profiles include simple profiles (coding of rectangular video frames), object-based profiles (coding of arbitrary-shaped visual objects), still texture profiles (coding of still images or texture ), scalable profiles (coding at multiple resolutions or quality levels) and studio profiles (coding for high-quality studio applications). In contrast with the highly flexible approach of MPEG-4 Visual, H.264 concentrates specifically on efficient compression of video frames. Key features of the standard include compression efficiency (providing significantly better compression than any previous standard), transmission efficiency (with a number of built-in features to support reliable, robust transmission over a range of channels and networks) and a focus on popular applications of video compression. Only three profiles are currently supported (in contrast to nearly 20 in MPEG-4 Visual), each targeted at a class of popular video communication applications. The Baseline profile may be particularly useful for conversational applications such as videoconferencing, the Extended profile adds extra tools that are likely to be useful for video streaming across networks and the Main profile includes tools that may be suitable for consumer applications such as video broadcast and storage. The MPEG-4 and H.264 Standards An understanding of the process of creating the standards can be helpful when interpreting or implementing the documents themselves. In this chapter we examine the role of the ISO MPEG and ITU VCEG groups in developing the standards. We discuss the mechanisms by which the features and parameters of the standards are chosen and the driving forces (technical and commercial) behind these mechanisms. We explain how to decode the standards and extract useful information from them and give an overview of the two standards covered by this book, MPEG-4 Visual (Part 2) [1] and H.264/MPEG-4 Part 10 [2]. Page No:1281

8 we concentrate on the target applications, the shape of each standard and the method of specifying the standard. We briefly compare the two standards with related International Standards such as MPEG-2, H.264 and JPEG. 5.2 DEVELOPING THE STANDARDS Creating, maintaining and updating the ISO/IEC ( MPEG-4 ) set of standards is the responsibility of the Moving Picture Experts Group (MPEG), a study group who develop standards for the International Standards Organisation (ISO). The emerging H.264 Recommendation (also known as MPEG-4 Part 10, Advanced Video Coding and formerly known as H.26L) is a joint effort between MPEG and the Video Coding Experts Group (VCEG), a study group of the International Telecommunications Union (ITU). MPEG developed the highly successful MPEG-1 and MPEG-2 standards for coding video and audio, now widely used for communication and storage of digital video, and is also responsible for the MPEG-6 standard and the MPEG-21 standardisation effort. VCEG was responsible for the first widely-used video telephony standard (H.261) and its successor, H.264, and initiated the early development of the H.26L project. The two groups set-up the collaborative Joint Video Team (JVT) to finalise the H.26L proposal and convert it into an international standard (H.264/MPEG- 4 Part 10) published by both ISO/IEC and ITU-T. and H.254 standards, providing better compression of video images. The new standard is entitled Advanced Video Coding (AVC) and is published jointly as Part 10 of MPEG-4 and ITU-T Recommendation H.254 [1, 4]. 6.RESULTS RESULT AND ANALYSIS FIG.1 INPUT VIDEO FOR COMPRESSION 5.3 H.264/MPEG INTRODUCTION The Moving Picture Experts Group and the Video Coding Experts Group (MPEG and VCEG) have developed a new standard that promises to outperform the earlier MPEG-4 Page No:1282

9 FIG 2 COMPRESSED VIDEO BY PROPOSED WORK FIG.3 COMPRESSION RATIO FOR ALL SELECTED FRAMES PERFORMANCE PARAMETRS: 1.BER_OF_MPEG4 = compression_ratio_of_mpeg4 = entropy_MPEG4 = CONCLUSION Proposed work is for comparative study of recent robust video compression standards. There is comparative study of H.264 and mpeg4 video compression standards. We used both subjective as well as objective quality assessment techniques to know the robustness of these two techniques. Although these two encoding format is used in different area due to different advantages and disadvantages, many people prefer H.264 to MPEG4 no matter in video quality, size or other aspects. Now, we begin to summarize why H.264 is more superior. 1. One of the advantages of H.264 is the high compression rate that is about 2 times more efficient than MPEG-4 encoding. To put it in another way, the high compression rate makes it possible to store more information on the same hard disk. 2. H.264 VS MPEG4 quality: The image quality of H.264 is better and playback is more fluent than MPEG4 compression. 3. H.264 owns more efficient mobile surveillance application. REFERENCES: [1] I. Richardson, Video Codec Design: Developing Image and Video Compression Systems, 1st ed. John Wiley & Sons, Ltd, [2] J. D. Gibson and A. Bovik, Eds., Handbook of Image and Video Processing, 1st ed. Orlando, FL, USA: Academic Press, Inc., [3] K. Jack, Video Demystified: A Handbook for the Digital Engineer, 5th ed. Newton, MA, USA: Newnes, [4] R. W. G. Hunt and P. M. R., Measuring Color, 4, Ed. John Wiley & Sons Inc., September [5] T. Wiegand, G. J. Sullivan, G. Bjøntegaard, and A. Luthra, Overview of the H.264/AVC video coding standard, IEEE Trans. Circuits Syst. Video Technol., vol. 13, no. 7, pp , [6] ITU-T Recommendation H.264 / ISO/IEC , Advanced Video Coding for Generic Audiovisual Services, ITU-T / ISO/IEC Std., March [7] Recommendation ITU-R BT.601-5, Studio encoding parameters of digital Page No:1283

10 television for standard 4:3 and wide-screen 16:9 aspect ratios,, ITU-T Std., [8] L. Hanzo, P. Cherriman, and J. Streit, Video Compression and Communications: From Basics to H.261, H.263, H.264, MPEG4 for DVB and HSDPA-Style Adaptive Turbo-Transceivers, 2nd ed. Wiley-IEEE Press, [9] S. B. Solak and F. Labeau, Sustainable ICTs and Management Systems for Green Computing. IGI Global, June 2012, ch. Green Video Compression for Portable and Low- Power Applications, pp [10] A. Malewar, A. Bahadarpurkar, and V. Gadre, A linear rate control model for better target buffer level tracking in H.264, Signal, Image and Video Processing, vol. 7, pp , [11] International telecommunication union-telecommunication, [12] International organization for standardization, [13] ITU-T Recommendation H.261, Video codec for audiovisual services at p X 64 kbit/s, ITU-T Std., December [14] ISO/IEC Standard , Information technology: coding of moving pictures and associated audio for digital storage media at up to about 1.5 Mbit/s-part 2: Video, ISO/IEC Std., [15] ISO/IEC Standard , Information technology: generic coding of moving pictures and associated audio information: Video, ISO/IEC Std., [16] ITU-T Recommendation H.262, Information technology - Generic coding of moving pictures and associated audio information: Video, ITU-T Std., July [17] ITU-T Recommendation H.263, Video coding for low bit rate communication, ITU- T Std., [18] M. G. Strinzis, Object-based coding of stereospic and 3D image sequences, IEEE Signal Process. Mag., pp , References [19] T. Ebrahimi and C. Horne, MPEG-4 natural video coding - an overview, Signal Processing: Image Communication, vol. 15, no. 4, pp , [20] ISO/IEC Standard , Information technology: coding of audiovisual objects-part 2: Visual, ISO/IEC Std., [21] ITU-T Recommendation H.265 / ISO/IEC , High Efficiency Video Coding (HEVC), ITU-T / ISO/IEC Std., October [22] F. Bossen, B. Bross, K. Suhring, and D. Flynn, HEVC complexity and implementation analysis, IEEE Trans. Circuits Syst. Video Technol., vol. 22, no. 12, pp , Dec [23] J. Vanne, M. Viitanen, T. D. Hamalainen, and A. Hallapuro, Comparative rate-distortion-complexity analysis of HEVC and AVC video codecs, IEEE Trans. Circuits Syst. Video Technol., vol. 22, no. 12, pp , Dec [24] M. B. Dissanayake and D. L. B. Abeyrathna, Performance comparison of HEVC and H.264/AVC standards in broadcasting environments, Information Processing Systems, vol. 11, no. 3, pp , September [25] I. E. Richardson, H.264 and MPEG-4 Video Compression: Video Coding for Nextgeneration Multimedia. John Wiley & Sons, Page No:1284

11 Page No:1285