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The Weissman score is a performance metric for lossless compression applications. It was developed by Tsachy Weissman, a professor at Stanford University, and Vinith Misra, a graduate student, at the request of producers for HBO's television series Silicon Valley, a television show about a fictional tech start-up working on a data compression algorithm.
When scaling a vector graphic image, the graphic primitives that make up the image can be scaled using geometric transformations with no loss of image quality. When scaling a raster graphics image, a new image with a higher or lower number of pixels must be generated. In the case of decreasing the pixel number (scaling down), this usually ...
Lagarith – Video codec designed for strong lossless compression in RGB(A) colorspace (similar to ZIP/RAR/etc.) libtheora – A reference implementation of the Theora format, based on VP3, part of the Ogg Project; Dirac as dirac-research, a wavelet based codec created by the BBC Research, and Schrödinger, an implementation developed by David ...
MPEG-4 SLS, or MPEG-4 Scalable to Lossless as per ISO/IEC 14496-3:2005/Amd 3:2006 (Scalable Lossless Coding), [1] is an extension to the MPEG-4 Part 3 (MPEG-4 Audio) standard to allow lossless audio compression scalable to lossy MPEG-4 General Audio coding methods (e.g., variations of AAC).
JPEG XS favors visually lossless quality in combination with low latency and low complexity, over crude compression performance. Hence, it is not a direct competitor to alternative image codecs like JPEG 2000 and JPEG XL or video codecs like AV1, AVC/H.264 and HEVC/H.265. Other important features are:
Typically, compressions using lossless operation mode can achieve around 2:1 compression ratio for color images. [5] This mode is quite popular in the medical imaging field, and defined as an option in DNG standard, but otherwise it is not very widely used because of complexity of doing arithmetics on 10, 12, or 14bpp values on typical embedded 32-bit processor and a little resulting gain in ...
Run-length encoding (RLE) is a form of lossless data compression in which runs of data (consecutive occurrences of the same data value) are stored as a single occurrence of that data value and a count of its consecutive occurrences, rather than as the original run. As an imaginary example of the concept, when encoding an image built up from ...
This is the normalization used by Matlab, for example, see. [99] In many applications, such as JPEG, the scaling is arbitrary because scale factors can be combined with a subsequent computational step (e.g. the quantization step in JPEG [100]), and a scaling can be chosen that allows the DCT to be computed with fewer multiplications. [101] [102]