Chapter 9:

MPEG

The basic scheme is to predict motion from frame to frame in the temporal direction, and then to use DCT's (discrete cosine transforms) to organize the redundancy in the

spatial directions. The DCT's are done on 8x8 blocks, and the motion prediction is done in the

luminance (Y) channel on 16x16 blocks. In other words, given the 16x16 block in the current frame that you are trying to code, you look for a close match to that block in a previous or future frame (there are backward prediction modes where later frames are sent first to allow interpolating between frames). The DCT coefficients (of either the actual data, or the difference between this block and the close match) are quantized, which means that you divide them by some value to drop bits off the bottom end. Hopefully, many of the coefficients will then end up being zero. The quantization can change for every

"macroblock" (a macroblock is 16x16 of Y and the corresponding 8x8's in both U and V). The results of all of this, which include the DCT coefficients, the motion vectors, and the quantization parameters (and other stuff) is Huffman coded using fixed tables. The DCT coefficients have a special Huffman table that is two-dimensional in that one code specifies a run-length of zeros and the non-

zero value that ended the run. Also, the motion vectors and the DC DCT components are DPCM, (subtracted from the last one) coded.

--Berkeley Multimedia Research Center MPEG-1 Document

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Apple VisualHub manual Mpeg

VisualHub specifications

Apple VisualHub was a versatile multimedia application designed for Mac OS X, aimed at simplifying the process of converting video files into various formats. Launched by a small developer known as TechSpaghetti, VisualHub quickly gained popularity due to its user-friendly interface and powerful functionality.

One of the main features of VisualHub was its ability to convert videos to a wide range of formats, including MP4, AVI, MPEG, and more. This flexibility allowed users to prepare video content for different devices such as iPhones, iPods, and Apple TV. The drag-and-drop feature enhanced user convenience by enabling users to simply drag video files into the application for immediate conversion.

VisualHub was built on a combination of robust technologies, leveraging FFmpeg, a popular multimedia framework, to handle video processing. This underlying technology empowered the application to support a diverse array of input formats and deliver high-quality output quickly. Additionally, VisualHub utilized a streamlined codebase that optimized performance and improved conversion speed compared to many of its competitors.

Another noteworthy characteristic of VisualHub was its batch processing capability. Users could efficiently convert multiple videos at once, saving valuable time, particularly for those who needed to process large collections of video files. This feature, coupled with its intuitive interface, made it accessible for both casual users and more advanced video enthusiasts.

In addition to conversion, VisualHub also offered basic editing capabilities, including trimming video clips and adjusting audio settings. This provided users with some level of customization before finalizing their videos.

Despite its many strengths, VisualHub faced challenges, particularly as the digital landscape evolved with the rise of cloud-based services and streaming platforms. However, its legacy as a user-friendly and efficient video conversion tool remains recognized among macOS users who sought a straightforward solution for handling their video files.

In conclusion, Apple VisualHub was a significant tool in the realm of multimedia applications for Mac, known for its extensive format support, batch processing, and ease of use. While it is no longer actively maintained or available for purchase, its impact on video conversion software continues to be appreciated by those who utilized it during its prime.