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Image Compression Experiments
Image compression is the application of Data compression on digital images. In effect, the objective is to reduce redundancy of the image data in order to be able to store or transmit data in an efficient form. 
Image compression can be lossy or lossless. Lossless compression is sometimes preferred for artificial images such as technical drawings, icons or comics. This is because lossy compression methods, especially when used at low bit rates, introduce compression artifacts. Lossless compression methods may also be preferred for high value content, such as medical imagery or image scans made for archival purposes. Lossy methods are especially suitable for natural images such as photos in applications where minor (sometimes imperceptible) loss of fidelity is acceptable to achieve a substantial reduction in bit rate. Methods for lossless image compression are:
Methods for lossy compression:
The best image quality at a given bit-rate (or compression rate) is the main goal of image compression. However, there are other important properties of image compression schemes: Scalability generally refers to a quality reduction achieved by manipulation of the bitstream or file (without decompression and re-compression). Other names for scalability are progressive coding or embedded bitstreams. Despite its contrary nature, scalability can also be found in lossless codecs, usually in form of coarse-to-fine pixel scans. Scalability is especially useful for previewing images while downloading them (e.g. in a web browser) or for providing variable quality access to e.g. databases. There are several types of scalability:
Region of interest coding. Certain parts of the image are encoded with higher quality than others. This can be combined with scalability (encode these parts first, others later). Meta information. Compressed data can contain information about the image which can be used to categorize, search or browse images. Such information can include color and texture statistics, small preview images and author/copyright information. Processing power. Compression algorithms require different amounts of processing power to encode and decode. Some high compression algorithms require high processing power. The quality of a compression method is often measured by the Peak signal-to-noise ratio. It measures the amount of noise introduced through a lossy compression of the image. However, the subjective judgement of the viewer is also regarded as an important, perhaps the most important measure. See also
External links
This article is licensed under the GNU Free Documentation License. It uses material from Wikipedia Encyclopedia article "Image Compression" |
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