Data compression
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Data compression reduces file size by encoding data more efficiently. It exploits redundancies in data like neighboring pixel values (spatial redundancy) or similar frames (temporal redundancy) in images and video. Compression can be lossless, preserving all information, or lossy, sacrificing some quality for higher compression ratios important for storage, transmission speed and bandwidth. Common lossless methods include run-length and Huffman coding while lossy techniques like JPEG, MP3 and MPEG are usually used for images, audio and video.
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Data compression
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Data compression reduces the size of a data file by identifying and eliminating statistical and perceptual redundancies. There are two main types: lossless compression, which reduces file size by encoding data more efficiently without loss of information, and lossy compression, which provides greater reduction by removing unnecessary data, resulting in information loss. Popular lossy audio and video compression formats like MP3, JPEG, and MPEG exploit patterns and limitations in human perception to greatly reduce file sizes for storage and transmission with minimal impact on quality. [/SUMMARY]
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Data compression
- 2. Table of contents • What is data compression? • The need of data compression. • What factors lead to data compression? • Methods of data compression.
- 3. What is data compression? • Data compression is the process of encoding data more efficiently to achieve a reduction in file size. • Data compression is a reduction in the number of bits needed to represent data. • Data compression is also called compaction. • Data may be Text, Image, Audio and Video
- 4. The need of data compression • Storage Space – Less storage space as size of file get reduced. • Transmission time – Less time taken as smaller size file transferred from source to destination. • Transmission speed. – Uploading and downloading of file take less time due to smaller size.
- 5. What factors lead to data compression? Redundancy refers to the amount of wasted space consumed by storage media to record picture information in a digital image. Image compression is achieved by exploiting redundancies in the image. These redundancies could be spatial, spectral, or temporal redundancy. Spatial redundancy: elements that are duplicated within a structure, such as neighboring pixels in a still image. Exploiting spatial redundancy is how compression is performed. Spectral redundancy is due to correlation between different color planes.
- 6. What factors lead to data compression?(Cont..) • Temporal redundancy: pixels in two video frames that have the same values in the same location. • Exploiting temporal redundancy is one of the primary techniques in video compression.
- 7. Methods of data compression. • There are two kinds of compression: Lossless and Lossy. • Lossless: – No Loss of Information • When we encode/decode, we get back original data. – Most widely used in text compression. – Compression ratio is very less.(3:1) • Compression ratio=uncompressed size(in bytes)/ compressed size(in bytes) – E.g. Run-length coding, Huffman coding, Arithmetic coding, Lempel-Zev-Welch(LZW)
- 8. Methods of data compression. • Lossy – Always loss of information. • When we encode/decode, we get back an approximation of the original data. – Most widely used in Image, Audio and Video compression. – Compression ratio is very high.(10:1) – E.g. JPEG(Joint photographic expert group): compressed image – MP3: compressed audio – MPEG(Motion picture expert group): compressed video