International Journal of Research ISSN NO:2236-6124 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 Recently, the exponential growth in saliency guided wavelet compression scheme networking technologies and widespread use for low-bitrate image/video coding of video content based multimedia applications. Important regions (faces in information over internet for mass security camera feeds, vehicles in traffic communication through social networking; surveillance) get degraded significantly at e-commerce, education, etc. have promoted low bitrates by existing compression the development of video coding to a great standards, such as JPEG/JPEG-2000/MPEG- extent. Various video coding schemes have 4, since these do not explicitly utilize any already been designed for seamless knowledge of which regions are salient. We transmission of digital video data and for design a compression algorithm which, given mass storage of digital information. The an image/video and a saliency value for each primary goal of a video coding standard is to pixel, computes a corresponding saliency achieve higher compression performance value in the wavelet transform domain. Our while maintaining high visual quality. A algorithm ensures wavelet coefficients human eye is space-variant non-uniform representing salient regions have a high resolution sampling system. Hence, saliency value. The coefficients are foveation based video coding yields higher transmitted in decreasing order of their compression performance by varying the saliency.This allows important regions in the visual quality of video data across the space image/video to have high fidelity even at very to match the non-uniform spatial sampling of low bitrates. Further, our compression a human eye. In the present doctoral research scheme can handle several salient regions work, efforts are made to develop fast and with different relative importance. We efficient foveated video compression compare the performance of our method with schemes that achieve higher compression the JPEG/JPEG-2000 image standards and performance as well as higher visual quality the MPEG-4 video standard through two at a lower computational complexity. experiments: face detection and vehicle tracking. We show improved detection rates 1.1 Digital Video and quality of reconstructed images/videos using our Saliency Based Compression Digital video is a three-dimensional data of a (SBC) algorithm. dynamic visual scene, sampled spatially and temporally. A visual scene temporally I.INTRODUCTION sampled at any time instant is known as a frame. Volume 7, Issue XI, November/2018 Page No:1275 International Journal of Research ISSN NO:2236-6124 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 Figure 1.1: Illustration of Spatio-temporal and adaptive video compression schemes sampling of a video scene are required to solve these issues [1]. A typical video coding system is shown in 1.2 Fundamentals of Video Figure 1.4. A video data generated at the Compression source is encoded with low bit-rate by a 1.2.1 Background video encoder. The compressed video data is In the modern world, the demand of video either sent to storage devices or transmitted data has increased manifold due to massive through a communication channel. At the internet application like social networking, receiving end, the compressed video data is e-governance, security and surveillance, decoded by a video decoder and video telephony. Hence, the network reconstructed video frames are displayed to bandwidth has become a major bottleneck users. for efficient 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 Figure 1.4: Typical video coding system important tools of a hybrid video transmission of these vast amount of video compression schemes. Various motion data in real-time even if the present estimation schemes are present in literature to technology offers quite large bandwidths. find out the best matched block in a reference Most probably, this problem will continue frame and enhance the compression for ever since the modern human civilization efficiency with minimum computation cost. will demand more and more for video In this chapter, some well-known, efficient, transmission applications in future. standard and benchmark schemes related to Therefore, a well designed and efficient different tools of efficient foveated video video compression system is always compression schemes, are studied. The required to reduce transmission bit-rate for proposed schemes, developed and designed video data content without degrading the in this doctoral research work, are compared visual quality significantly. In a against these in subsequent chapters. heterogeneous network, where medium to Therefore, attempts are made here for a low data rates are supported, transmission of detailed and critical analysis of these video data is even a more challenging task. schemes. The literature review is categorized Volume 7, Issue XI, November/2018 Page No:1276 International Journal of Research ISSN NO:2236-6124 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 Figure 2.1: Categorisation of literature from the fixation points, it delivers review perceptually high quality at greatly reduced bandwidths. There are several efficient Wallace et al. [5] and Kortum and Geisler [4] foveated video processing schemes available have shown geometric transformation of in literature, for example, foveation filtering uniform sampled image to non-uniform space (local bandwidth reduction) [4], saliency variant sampled image using super pixel. The detection based foveating [6] and wavelet super pixels are generated to match the retinal based foveated compression [3]. sampling distribution by grouping and averaging the uniform pixels. Lee and Bovik In 1993, Silsbee et al. have introduced the have shown that foveation is a coordinate image coding based on the properties of transformation from cartesian coordinates to human visual system (HVS) [4]. The video is curvilinear coordinates and a local bandwidth encoded by dividing the frame into a number is uniformly distributed over curvilinear of spatio-temporal patterns which are based coordinates for a foveated image [5]. on spatio-temporal properties of HVS. The adaptation of foveated processing to various 2.2 Directional Transforms video coding standards is demonstrated by [2]. The recent developments in video acquisition and display systems and exponential growth Broadly, foveation method can be classified in transmission bandwidths have increased into three categories: the demand of superior quality video contents 1. Geometry based foveation (GBF), in multimedia applications with resolutions ranging from 166 × 144 pixels (QCIF) to 2. Filtering based foveation (FBF) and 3840 × 2160 pixels (UHD). With widespread adoption of emerging applications like video 3. multi-resolution based foveation (MBF). streaming, video surveillance, blue-ray disk video, etc. video compression has become an In GBF schemes, uniformly sampled image integral component of such multimedia coordinates are transformed into spatial applications. variant coordinates by log map transform, also known as foveation coordinate However, a video data in an uncompressed transform, which exploits the retina sampling format demands a huge amount of storage geometry [5]. space and transmission bandwidth. To Volume 7, Issue XI, November/2018 Page No:1277 International Journal of Research ISSN NO:2236-6124 surpass these physical constraints, an single, low-resolution, uncompressed stream. efficient video compression scheme is always Even with constant advances in storage and required. Various video coding methods have transmission capacity, compression is likely been developed in literature to accomplish to be an essential component of multimedia video compression such as entropy coding services for many years to come. [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. 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