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  2. LosslessCut - Wikipedia

    en.wikipedia.org/wiki/LosslessCut

    LosslessCut is a free, platform independent video editing software, which supports numerous audio, video and container formats. [4] [5]It is a graphical user interface, with MacOS, [6] Windows [7] and Linux [8] support, using the FFmpeg multimedia framework.

  3. Lossy compression - Wikipedia

    en.wikipedia.org/wiki/Lossy_compression

    While data reduction (compression, be it lossy or lossless) is a main goal of transform coding, it also allows other goals: one may represent data more accurately for the original amount of space [5] – for example, in principle, if one starts with an analog or high-resolution digital master, an MP3 file of a given size should provide a better ...

  4. JPEGmini - Wikipedia

    en.wikipedia.org/wiki/JPEGmini

    It designed to reduce the file size of images and videos with limited quality reduction. [1 ... AAC audio tracks in MP4, M4V or MOV containers, with files up to 800 ...

  5. Lossless compression - Wikipedia

    en.wikipedia.org/wiki/Lossless_compression

    In fact, if we consider files of length N, if all files were equally probable, then for any lossless compression that reduces the size of some file, the expected length of a compressed file (averaged over all possible files of length N) must necessarily be greater than N. [citation needed] So if we know nothing about the properties of the data ...

  6. Comparison of video codecs - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_video_codecs

    The quality the codec can achieve is heavily based on the compression format the codec uses. A codec is not a format, and there may be multiple codecs that implement the same compression specification – for example, MPEG-1 codecs typically do not achieve quality/size ratio comparable to codecs that implement the more modern H.264 specification.

  7. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    Data compression aims to reduce the size of data files, enhancing storage efficiency and speeding up data transmission. K-means clustering, an unsupervised machine learning algorithm, is employed to partition a dataset into a specified number of clusters, k, each represented by the centroid of its points.