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May 17, 2015




  • 1. Data compression (bit-rate reduction) involves encoding information using fewer bits than the original representation. The process of reducing the size of a data file is popularly referred to as data compression, although its formal name is source coding (coding done at the source of the data before it is stored or transmitted).[ Compression can be either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by identifying unnecessary information and removing it.

2. The lossless data compression method essentially has two steps: Analyze the files and then eliminate the redundant data found within them. For example, if a file compressor analyzed and eliminated all the repeated words in a document file, the result would be a document with about 60 percent fewer words. Such is the case with compressed files. Your application analyzes the file and removes all the equivalent superfluous data bits, and shrinks the overall size of the file. However, if you attempted to read the article with the omitted words, it wouldn't make any sense. Therefore, the file compression applications insert placeholders where those eliminated words were. When you extract the file, the application automatically restores the repeated words to their places, making the file readable. Because no data is lost, this method is called lossless compression. 3. Lossy data compression is the converse of lossless data compression. In these schemes, some loss of information is acceptable. Dropping nonessential detail from the data source can save storage space. Lossy data compression schemes are informed by research on how people perceive the data in question. For example, the human eye is more sensitive to subtle variations inluminance than it is to variations in color. JPEG image compression works in part by rounding off nonessential bits of information. There is a corresponding trade-off between information lost and the size reduction. A number of popular compression formats exploit these perceptual differences, including those used in music files, images, and video. 4. Data compression works by finding patterns in data that occur frequently, and changing their representation to something short, so that the total amount of data is reduced without sacrificing any useful information. For example, suppose you have a stream of data that consists of only ones and zeros, like this: 10100001010101001. And suppose that you know that this data stream usually contains a lot more zeros than ones; that is, a stream is more likely to be 100000100000101000000 than 111110111011011111. In this case, you can develop a way of abbreviating the zeros so that they take up less space. You can define A as representing a one, B as representing a single zero, and C as representing four consecutive zeros. Now suppose you have a data stream like this: 100000100100000000000001010010000 5. After you encode it, it will look like ACBABBACCCBABABBAC. Notice that this is shorter than the original, because your encoding method helped abbreviate long strings of consecutive zeros. This is data compression.In order for data compression to work, the data stream must not be random. There has to be some sort of pattern in it, or you can't compress it. For example, if the stream contains ones and zeros, but there's no pattern, and neither ones nor zeroes are more common, then you can't compress the data stream, because there's nothing predictable about it.If you want a more formal definition, data compression consists of a way of encoding a set of input messages into a set of output messages such that the most common input messages encode to the shortest output messages, and the least common input messages encode to the longest output messages. As long as the input messages are not randomly distributed, this will result in an output stream that is shorter than the input stream. It's all information theory. 6. The objective of image compression is to reduce irrelevance and redundancy of the image data in order to be able to store or transmit data in an efficient form. Image compression may be lossy or lossless. 7. Lossless compression is preferred for archival purposes and often for medical imaging, technical drawings, clip art, or comics. Lossless compression is possible because most real-world data has statistical redundancy. For example, an image may have areas of colour that do not change over several pixels; instead of coding "red pixel, red pixel, ..." the data may be encoded as "279 red pixels". This is a basic example of run-length encoding; there are many schemes to reduce file size by eliminating redundancy. 8. Methods for lossless image compression are: Run-length encoding used as default method in PCX and as one of possible in BMP, TGA, TIFF DPCM and Predictive Coding Entropy encoding Adaptive dictionary algorithms such as LZW used in GIF and TIFF Deflation used in PNG, MNG, and TIFF Chain codes 9. Lossy compression methods, especially when used at low bit rates, introduce compression artifacts. Lossy methods are especially suitable for natural images such as photographs in applications where minor (sometimes imperceptible) loss of fidelity is acceptable to achieve a substantial reduction in bit rate. The lossy compression that produces imperceptible differences may be called visually lossless. Lossy image compression can be used in digital cameras, to increase storage capacities with minimal degradation of picture quality. Similarly, DVDs use the lossy MPEG-2 Video codec for video compression. 10. Methods for lossy compression: Reducing the color space to the most common colors in the image. The selected colors are specified in the color palette in the header of the compressed image. Each pixel just references the index of a color in the color palette, this method can be combined with dithering to avoid posterization. In contrast to lossless compression, which retains the integrity of the original file, the so-called lossy data compression method scans the file being compressed to determine what information the file can do without. It then eliminates those bits completely, with no method to retrieve that data. This method is akin to taking picture with your camera phone, opening a photo-editing app, cropping off the edges of the picture and then sending it to a friend. The recipient of that message cannot restore the pixels you cropped off before you sent the image. Such is the case with lossy compression. While this is method is more effective at reducing the size of the file, you won't be able to restore the file to its original state when you extract the file on the back end of the process. 11. What is the so-called image compression coding?To store the image into bit-stream as compact as possible and to display the decoded image in the monitor as exact as possible. 12. The image file is converted into a series of binary data, which is called the bit-stream. The decoded receives the encoded bitstream and decoded it to reconstruct the image. The total data quantity of the bit-stream is less than the total data quantity of the original image. 13. GIF Graphics Interchange Format Compressed but do not lose any of the original data (loseless) Limited to 256 colors Still patented in a few countries PNG Portable Network Graphics Up to 48 bits worth of color New graphic format 14. JPEG: Joint Photographic Experts Group an international standard since 1992. Compresses the data but can lose some of the original content (lossy). Contains millions of colors. Works with colour and greyscale images. Up to 24 bit colour images (Unlike GIF) Target photographic quality images (Unlike GIF) Suitable for many applications e.g.,satellite, medical, general photography. 15. Audio compression is a way to reduce the size of the audio file. A form of data compression designed to reduce the size of audio files Audio compression can be lossless or lossy Audio compression algorithms are typically referred to as audio codecs. 16. 2 types of Audio Compression Lossless - allows one to preserve an exact copy of one's audio files Usage: For archival purposes, editing, audio quality. Lossy - irreversible changes , achieves far greater compression, use psychoacoustics to recognize that not all data in an audio stream can be perceived by the human auditory system. Usage: distribution of streaming audio, or interactive applications 17. Codecs: LosslessLossyFree Lossless Audio Codec (FLAC)MP2- MPEG-1Layer 2 audio codecApple LosslessMP3 MPEG-1 Layer 3 audio codecMPEG-4 ALSMPC MusepackMonkey's AudioVorbis Ogg VorbisLossless Predictive Audio Compression (LPAC)AAC Advanced Audio Coding (MPEG-2 and MPEG-4)Lossless Transform Audio Compression (LTAC)WMA Windows Media Audio AC3 AC-3 or Dolby Digital A/52 18. Motion Picture Experts Group An ISO standard for high-fidelity audio compression. An ISO/IEC working group, established in 1988 to develop standards for digital audio and video formats. 19. MPEG-1-Designed for up to 1.5 Mbit/sec. Is used to compress video and is designed for specially for Video CD (VCD).MPEG-2--Designed for between 1.5 and 15 Mbit/sec. Similar to MPEG-1, but it can be used for more applications. Transmission rates are more than double the transmission for MPEG-1. Works with HDTV and DVD. 20. ---MPEG-4Designed specially for the Internet. Provides greater audio and video interactivity than previous MPEG versions. It allows developers to control objects independently in a scene. MPEG-4 includes the capability of representing natural and synthesized sound and also support natural textures, images, photograph, natural video and animated video. 21. Audio InputTime to Frequency Mapping Filter bankPsychoacoustic ModelBit Allocation, Qu antize and codingBit stre