The MPEG Representation of Digital Media

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Field dominance is relevant when transferring data in such a way that frame boundaries must be known and preserved, such as:. Field dominance defines the order of fields in a frame and can be either F1 dominant or F2 dominant. F1 dominant specifies a frame as an F1 field followed by an F2 field. F2 dominant specifies a frame as an F2 field followed by an F1 field. This is the protocol followed by several New York production houses for the line formats only. Most older VTRs cannot make edits on any granularity finer than the frame. The latest generation of VTRs are able to make edits on arbitrary field boundaries, but can and most often are configured to make edits only on frame boundaries.

Video capture or playback on a computer, when triggered, must begin on a frame boundary. Software must interlace two fields from the same frame to produce a picture. When software deinterlaces a picture, the two resulting fields are in the same frame. Regardless of the field dominance, if there are two contiguous fields in a VLBuffer, the first field is always temporally earlier than the second one: Under no circumstances should the temporal ordering of fields in memory be violated. The terms even and odd can refer to whether a field's active lines end up as the even scanlines of a picture or the odd scanlines of a picture.

In this case, you need to additionally specify how the scanlines of the picture are numbered beginning with 0 or beginning with 1 , and you may need to also specify vs. Even and odd could also refer to the number 1 or 2 in F1 and F2, which is of course a different concept that only sometimes maps to the notion of whether a field's active lines end up as the even scanlines of a picture or the odd scanlines of a picture.

This definition seems somewhat more popular. The way in which two consecutive fields of video should be interlaced to produce a picture depends on. Line numbering in memory does not necessarily correspond to the line numbers in a video specification. Software line numbering can begin with either a 0 or 1. Picture line numbering scheme in software is shown both 0-based like the Movie Library and 1-based. For line analog signals, the picture should be produced in this manner F1 has active lines, F2 has active lines, totaling active lines :.

For official line digital signals, the picture should be produced in this manner F1 has active lines, F2 has active lines, totaling active lines :. For practical line digital signals, all current Silicon Graphics video hardware skips line 20 of the signal and pretends that the signal has active lines. As a result, you can think of the digital signal as having exactly the same interlacing characteristics and line numbers as the analog signal F1 has active lines and F2 has active lines, totaling active lines :.

For line analog signals, the picture should be produced in this manner F1 has active lines, F2 has active lines :. For line digital signals, the picture should be produced in this manner F1 has active lines, F2 has active lines :. Both of the digital specs use identical line numbering to their analog counterparts. However, Video Demystified and many chip specifications use nonstandard line numbers in some not all of their diagrams. A word of caution: M draws fictitious half-lines in its figure 3 in places that do not correspond to where the half-lines fall in the analog signal.

This section describes digital image data attributes and how to use them. Image attributes can apply to the image as a whole, to each pixel, or to a pixel component. Not all of the libraries require or use all of the DM image parameters. Clones of some DM image parameters can be found in vl. These attributes and the parameters that represent them are discussed in detail in the sections that follow. Video streams and movie files contain a number of individual images of uniform size. The image size of a video stream or a movie file refers to the height and width of the individual images contained within it, and is often referred to as frame size.

Some image formats require that the image dimensions be integral multiples of a factor, necessitating either cropping or padding of images that don't conform to those requirements.

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Pixels aren't always perfectly square, in fact they often aren't. The shape of the pixel is defined by the pixel aspect ratio. Square pixels have a pixel aspect ratio of 1. Whether a conversion is necessary or optimal depends on the original image source, the final destination, and, to a certain extent, the hardware path transporting the signal. For example, the digital sampling of analog video in accordance to Rec. On the other hand, graphics displays render each pixel as square. This means that a Rec. Conversely, computer-originated digital video x and x displays incorrectly when sent to video out in nonsquare mode, but displays correctly when sent to an onscreen graphics window or to video out in square mode.

Some Silicon Graphics video devices sample natively using only one format, either square or nonsquare, and some Silicon Graphics video devices filter signals on certain connectors. See the video device reference pages for details. Software filtering is also possible. Compression is a method of encoding data more efficiently without changing its content significantly.

In some cases such as MPEG, the codec also defines a standard file format in which to contain data of that format. Otherwise, there is a set of file formats that can hold data of that format. Stateful codecs are hard to use in an editing environment but generally produce better compression results because they get access to more redundancy in the data.

The algorithm then compresses each region independently. Tile-based algorithms are notorious for producing output with visible blocking artifacts at the tile boundaries. Some algorithms specify that the output is to be blurred to help hide the artifacts.

Such algorithms generally do a very good job at compressing images. The computational cost of the transformation is generally high, so:. Transform-based algorithms are typically also tile-based algorithms since the computation is easier on small tiles , and thus suffer the artifacts of tile-based algorithms.

For most compression algorithms, the compressed data stream is designed so that the video can be played forward or backward, but some compression schemes, such as MPEG, are predictive and so are more efficient for forward playback. Although any algorithm can be used for still video images, the JPEG Joint Photographic Experts Group -baseline algorithm, which is referred to simply as JPEG for the remainder of this guide, is the best for most applications.

JPEG is a compression standard for compressing full-color or grayscale digital images. It is a lossy algorithm, meaning that the compressed image is not a perfect representation of the original image, but you may not be able to detect the differences with the naked eye. Because each image is coded separately intra-coded , JPEG is the preferred standard for compressed digital nonlinear editing.

JPEG is based on psychovisual studies of human perception: Image information that is generally not noticeable is dropped out, reducing the storage requirement anywhere from 2 to times. JPEG is most useful for still images; it is usable, but slow when performed in software, for video. Silicon Graphics hardware JPEG accelerators are available for compressing video to and decompressing video from memory, or for compressing to and decompressing from a special video connection to a video board.

The typical use of JPEG is to compress each still frame during the writing or editing process, with the intention of applying another type of compression to the final version of the movie or to leave it uncompressed. JPEG works better on high-resolution, continuous-tone images such as photographs, than on crisp-edged, high-contrast images such as line drawings. The amount of compression and the quality of the resulting image are independent of the image data.

The quality depends on the compression ratio. You can select the compression ratio that best suits your application needs. For more information, see jpeg 4. See also Pennebaker, William B. The MPEG-1 systems specification defines multiplexing for compressed audio and video bitstreams without performing additional compression.

An MPEG-1 encoded systems bitstream contains compressed audio and video data that has been packetized and interleaved along with timestamp and decoder buffering requirements. MPEG-1 allows for multiplexing of up to 32 compressed audio and 16 compressed video bitstreams. Each bitstream type has its own syntax, as defined by the standard.

MPEG-1 video uses a technique called motion estimation or motion search , which compresses a video stream by comparing image data in nearby image frames. For example, if a video shows the same subject moving against a background, it's likely that the same foreground image appears in adjacent frames, offset by a few pixels.

Images from the intervening frames can then be reconstructed by combining the offset data with the keyframe data. P predictive frames, which require information from previous P or I frames in order to be decoded. P frames are also sometimes considered forward reference frames because they contain information needed to decode other P frames later in the video bitstream. You must first display I 0 and retain its information in order to decode P 3 , but you cannot yet display P 3 because you must first decode and display the two between frames B 1 and B 2 , which also require information from P 3 , as well as from each other, to be decoded.

Once B 1 and B 2 have been decoded and displayed, you can display P 3 , but you must retain its information in order to decode P 6 , and so on. MPEG is an asymmetric coding technique—compression requires considerably more processing power than decompression because MPEG examines the sequence of frames and compresses them in an optimized way, including compressing the difference between frames using motion estimation.

This makes MPEG well suited for video publishing, where a video is compressed once and decompressed many times for playback. Because MPEG is a predictive scheme, it is tuned for random access editing due to its inter-coding, or for forward playback rather than backward. Run-length encoding RLE compresses images by replacing pixel values that are repeated for several pixels in a row with a single pixel at the first occurrence of a particular value, followed by a run-length a count of the number of subsequent pixels of the same value every time the color changes.

Although this algorithm is lossless, it doesn't save as much space as the other compression algorithms—typically less than compression is achieved.

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It is a good technique for animations where there are large areas with identical colors. It is the only algorithm currently available to directly compress 8-bit RGB data. MVC is a color-cell compression technique that works well for video, but can cause fuzzy edges in high-contrast animation.

There are 2 versions:. A fairly lossy algorithm that does not produce compression ratios as high as JPEG, but it is well suited to movies. Provides results similar to MVC1 in terms of image quality. Movies compressed with QuickTime store and play picture tracks and soundtracks independently of each other, analogous to the way the Movie Library stores separate image and audio tracks. You can't work with pictures and sound as separate entities using the QuickTime Starter Kit utilities on the Macintosh, but you can use the Silicon Graphics Movie Library to work with the individual image and audio tracks in a QuickTime movie.

QuickTime movie soundtracks are playable on Macintosh and Silicon Graphics computers, but each kind of system has a unique audio data format, so audio playback is most efficient when using the native data format and rate for the computer on which the movie is playing. Apple None. Both the number of colors and the recording quality can affect the size of the movie.

Apple Photo. JPEG is best suited for compressing individual still frames, because decompressing a JPEG image can be a time-consuming task, especially if the decompression is performed in software. JPEG is typically used to compress each still frame during the writing or editing process, with the intention of applying another type of compression to the final version of the movie or leaving it uncompressed.

Apple Animation. Apple Animation uses a lossy run-length encoding RLE method, which compresses images by storing a color and its run-length the number of pixels of that color every time the color changes. Apple Animation is not a true lossless RLE method because it stores colors that are close to the same value as one color.

This method is most appropriate for compressing images such as line drawings that have highly contrasting color transitions and few color variations. Apple Video. Apple Video uses a method whose objective is to decompress and display movie frames as fast as possible. It compresses individual frames and works better on movies recorded from a video source than on animations.

Cinepak developed by Radius, Inc. The Cinepak format is designed to control its own bitrate, and thus it is extremely common on the World Wide Web and is also used in CD authoring. Cinepak is not a transform-based algorithm. The codebook evolves over time as the image changes, thus this algorithm is stateful. Compressed data isn't always a perfect representation of the original data. Information can be lost in the compression process. A lossless compression method retains all of the information present in the original data.

Algorithms can be either numerically lossless or mathematically lossless. Numerically lossless means that the data is left intact. Mathematically lossless means that the compressed data is acceptably close to the original data. Image quality is a measure of how true the compression is to the original image. Image quality is one of the conversion controls that you can specify for an image converter. Image quality is specified in both the spatial and temporal domains.

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In a spatial approximation, pixels from a single image are compared to each other, and identical or similar pixels are noted as repeat occurrences of a stored representative pixel. In a temporal approximation, pixels from an image stream are compared across time, and identical or similar pixels are noted as repeat occurrences of a stored representative pixel, but offset in time.

Quality values range from 0 to 1. You can set both quality factors numerically, or you can use the following rule-of-thumb factors to set quality informally:. These quality factors can be assigned to intermediate steps in the slider or thumbwheel to give the impression of infinitely adjustable quality. The compression ratio is a tradeoff between the quality and the bitrate. Adjusting either one of these parameters affects the other, and, if both are set, bitrate usually takes precedence in the Silicon Graphics Digital Media Libraries.

The picture quality is then adjusted to achieve the stated rate. Some Silicon Graphics algorithms guarantee the bitrate, some try to achieve the stated rate, and some do not support a bitrate parameter. The Digital Media Libraries have their own terminology to define three types of frames possible in a motion estimation compression method:. Also called I frame or keyframe. Also called reference frame, P predictive frame, or delta frame.

Also called B frame. Image orientation refers to the relative ordering of the horizontal scan lines within an image. The scanning order depends on the image source and can be either top-to-bottom or bottom—to—top, but it is important to know which. Video and compressed video is typically oriented top-to-bottom. Interlacing is a video display technique that minimizes the amount of video data necessary to display an image by exploiting human visual acuity limitations. Interlacing weaves alternate lines of two separate fields of video at half the scan rate.

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Generally, interlacing refers to a technique for signal encoding or display, and interleaving refers to a method of laying out the lines of video data in memory. Interleaving can also refer to how the samples of an image's different color basis vectors are arranged in memory, or how audio and video are arranged together in memory. A movie file encodes pairs of fields into what it calls frames, and all data transfers are on frame boundaries.

A two-field image in a movie file does not always represent a complete video frame because it could be clipped or not derived from video. This is further complicated by that fact that both top-to-bottom and bottom-to-top ordering of video lines in images are supported. For a signal with F1 dominance, a frame consists of an F1 field followed by an F2 field temporally and in memory.

However, if the signal has F2 dominance, where a frame consists of F2 followed by F1, the first field is now an F2 field so:. This is the typical image layout for most image data. Both are passthrough formats; they are intended for use with image data that is passed untouched from a Silicon Graphics graphics or video input source directly to hardware.

This section describes image attributes that are specified on a per-pixel or per-pixel-component basis. Pixel packing formats define the bit ordering used for packing image pixels in memory. Native packings are supported directly in hardware. In other words, native packings don't require a software conversion. Conversion of information to digital form is a prerequisite for this enhanced machine role, but must be done having in mind requirements such as compactness, fidelity, interpretability etc.

This book provides an overview of the basic technology and mechanisms underpinning the operation of MPEG standards. It is a valuable reference for those making decisions in products and services based on digital media, those with general background, engaged in studies or developments of MPEG-related implementations, and those curious about MPEG and its role in the development of successful, standard technologies. Skip to main content Skip to table of contents. Advertisement Hide. Daniel Page. Next-Generation Video Coding and Streaming. Benny Bing.

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Antonio Carlos Schneider Beck. Practical Computer Vision. Abhinav Dadhich. Measuring Signal Generators. Multimedia Computing. Gerald Friedland. Ernest Mendrela. Fundamental Data Compression. Ida Mengyi Pu. Erick Gonzalez Rodriguez. Video Over Wireless. Kaveh Hosseini. Amir Zjajo. Terrence Blevins. Real-Time Digital Signal Processing.

The MPEG Representation of Digital Media The MPEG Representation of Digital Media
The MPEG Representation of Digital Media The MPEG Representation of Digital Media
The MPEG Representation of Digital Media The MPEG Representation of Digital Media
The MPEG Representation of Digital Media The MPEG Representation of Digital Media
The MPEG Representation of Digital Media The MPEG Representation of Digital Media
The MPEG Representation of Digital Media The MPEG Representation of Digital Media

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