This form of quantization, where all values in the interval, n ⋅ k + ] are mapped to n ⋅ k, is a special case of uniform quantization. Near-lossless compression could potentially lead to significant increase in compression, thereby giving more efficient utilization of precious bandwidth while preserving the integrity of the images with respect to the postprocessing operations that are carried out. Based on these guarantees, a scientist can be assured that the extracted parameters of interest will either not be affected or be affected only within a bounded range of error. This leads to the notion of a near-lossless compression technique that gives quantitative guarantees about the type and amount of distortion introduced. The uncertainty about reconstruction errors introduced by a lossy compression technique is undesirable. In such applications, the image is subjected to postprocessing to extract parameters of interest like ground temperature or vegetation indices. However, in many applications, the end-use of the image is not human perception. On the other hand, state-of-the-art lossy compression techniques give compression rations in excess of 20:1 with virtually no loss in visual fidelity. Typically, depending on the image, lossless compression ratios range from about 1.5:1 to 3:1. Ansari Rashid, in Handbook of Image and Video Processing (Second Edition), 2005 3.6 Near-Lossless CompressionĪlthough lossless compression is required in many applications, compression ratios obtained with lossless techniques are significantly lower than those possible with lossy compression. The advantage of lossy methods over lossless methods is that in some cases a lossy method can produce a much smaller compressed file than any known lossless method, while still meeting the requirements of the application. Depending on the design of the format, lossy data compression often suffers from generation loss, that is, compressing and decompressing multiple times will do more damage to the data than doing it once. This is in contrast with lossless data compression. Lossy methods are most often used for compressing sound, images, or videos. These methods are typically referred to as codecs in this context. With this method, compressing data and then decompressing it may result in it being different from the original, but “close enough” to be useful somehow. However, a lossy data compression method approaches by another way. Lossless compression is also handy for storing files as they take up less volume.

This makes lossless compression convenient for transferring files across the network, as smaller files transfer faster. If an original file is 1.5 MB, for example, lossless compression can reduce it to about half that size, depending on the type of file being compressed.

Lossless compression “packs” data into a smaller file size by using a kind of internal shorthand to signify redundant data.

Lossless compression is a compression technique that does not lose any data in the compression process. Peng Zhang, in Industrial Control Technology, 2008 6.4.4.1 Loss and Lossless Compression and Decompression

History of image compression standards