Sum Of Absolute Transformed Differences
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Sum Of Absolute Transformed Differences
The sum of absolute transformed differences (SATD) is a block matching criterion widely used in fractional motion estimation for video compression. It works by taking a frequency transform, usually a Hadamard transform, of the differences between the pixels in the original block and the corresponding pixels in the block being used for comparison. The transform itself is often of a small block rather than the entire macroblock. For example, in x264, a series of 4×4 blocks are transformed rather than doing the more processor-intensive 16×16 transform. Comparison to other metrics SATD is slower than the sum of absolute differences (SAD), both due to its increased complexity and the fact that SAD-specific MMX and SSE2 instructions exist, while there are no such instructions for SATD. However, SATD can still be optimized considerably with SIMD instructions on most modern CPUs. The benefit of SATD is that it more accurately models the number of bits required to transmit the resid ...
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Motion Estimation
Motion estimation is the process of determining ''motion vectors'' that describe the transformation from one 2D image to another; usually from adjacent frames in a video sequence. It is an ill-posed problem as the motion is in three dimensions but the images are a projection of the 3D scene onto a 2D plane. The motion vectors may relate to the whole image (global motion estimation) or specific parts, such as rectangular blocks, arbitrary shaped patches or even per pixel. The motion vectors may be represented by a translational model or many other models that can approximate the motion of a real video camera, such as rotation and translation in all three dimensions and zoom. Related terms More often than not, the term motion estimation and the term ''optical flow'' are used interchangeably. It is also related in concept to ''image registration'' and '' stereo correspondence''. In fact all of these terms refer to the process of finding corresponding points between two images or vi ...
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Theora
Theora is a free file format, free Lossy compression, lossy video compression format. It is developed by the Xiph.Org Foundation and distributed without licensing fees alongside their other free and open media projects, including the Vorbis audio format and the Ogg container. The libtheora video codec is the reference implementation (computing), reference implementation of the Theora video compression format being developed by the Xiph.Org Foundation. Theora is derived from the formerly Proprietary software, proprietary VP3 codec, released into the public domain by On2 Technologies. It is broadly comparable in design and bitrate efficiency to MPEG-4 Part 2, early versions of Windows Media Video, and RealVideo while lacking some of the features present in some of these other codecs. It is comparable in open standards philosophy to the BBC's Dirac (video compression format), Dirac codec. Theora is named after Theora Jones, Edison Carter's Controller on the ''Max Headroom (TV ...
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Video Compression
In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Typically, a device that performs data compression is referred to as an encoder, and one that performs the reversal of the process (decompression) as a decoder. The process of reducing the size of a data file is often referred to as data compression. In the context of data transmission, it is called source coding; encoding done at the source of the data before it is stored or transmitted. Source coding should not be confused with channel coding, for error detection and correction or line coding, the means for mapping data onto a signal. C ...
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Sum Of Absolute Differences
In digital image processing, the sum of absolute differences (SAD) is a measure of the similarity between image blocks. It is calculated by taking the absolute difference between each pixel in the original block and the corresponding pixel in the block being used for comparison. These differences are summed to create a simple metric of block similarity, the ''L''1 norm of the difference image or Manhattan distance between two image blocks. The sum of absolute differences may be used for a variety of purposes, such as object recognition, the generation of disparity maps for stereo images, and motion estimation for video compression. Example This example uses the sum of absolute differences to identify which part of a search image is most similar to a template image. In this example, the template image is 3 by 3 pixels in size, while the search image is 3 by 5 pixels in size. Each pixel is represented by a single integer from 0 to 9. Template Search image 2 5 5 2 7 5 ...
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Motion Estimation
Motion estimation is the process of determining ''motion vectors'' that describe the transformation from one 2D image to another; usually from adjacent frames in a video sequence. It is an ill-posed problem as the motion is in three dimensions but the images are a projection of the 3D scene onto a 2D plane. The motion vectors may relate to the whole image (global motion estimation) or specific parts, such as rectangular blocks, arbitrary shaped patches or even per pixel. The motion vectors may be represented by a translational model or many other models that can approximate the motion of a real video camera, such as rotation and translation in all three dimensions and zoom. Related terms More often than not, the term motion estimation and the term ''optical flow'' are used interchangeably. It is also related in concept to ''image registration'' and '' stereo correspondence''. In fact all of these terms refer to the process of finding corresponding points between two images or vi ...
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Motion Compensation
Motion compensation in computing, is an algorithmic technique used to predict a frame in a video, given the previous and/or future frames by accounting for motion of the camera and/or objects in the video. It is employed in the encoding of video data for video compression, for example in the generation of MPEG-2 files. Motion compensation describes a picture in terms of the transformation of a reference picture to the current picture. The reference picture may be previous in time or even from the future. When images can be accurately synthesized from previously transmitted/stored images, the compression efficiency can be improved. Motion compensation is one of the two key video compression techniques used in video coding standards, along with the discrete cosine transform (DCT). Most video coding standards, such as the H.26x and MPEG formats, typically use motion-compensated DCT hybrid coding, known as block motion compensation (BMC) or motion-compensated DCT (MC DCT). Function ...
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VC-1
SMPTE 421, informally known as VC-1, is a video coding format. Most of it was initially developed as Microsoft's proprietary video format Windows Media Video 9 in 2003. With some enhancements including the development of a new Advanced Profile, it was officially approved as a SMPTE standard on April 3, 2006. It was primarily marketed as a lower-complexity competitor to the H.264/MPEG-4 AVC standard. After its development, several companies other than Microsoft asserted that they held patents that applied to the technology, including Panasonic, LG Electronics and Samsung Electronics. VC-1 is supported in the now-deprecated Microsoft Silverlight, the briefly-offered HD DVD disc format, and the Blu-ray Disc format. Format VC-1 is an evolution of the conventional block-based motion-compensated hybrid video coding design also found in H.261, MPEG-1 Part 2, H.262/MPEG-2 Part 2, H.263, and MPEG-4 Part 2. It was widely characterized as an alternative to the ITU-T and MPEG video cod ...
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Microsoft
Microsoft Corporation is an American multinational technology corporation producing computer software, consumer electronics, personal computers, and related services headquartered at the Microsoft Redmond campus located in Redmond, Washington, United States. Its best-known software products are the Windows line of operating systems, the Microsoft Office suite, and the Internet Explorer and Edge web browsers. Its flagship hardware products are the Xbox video game consoles and the Microsoft Surface lineup of touchscreen personal computers. Microsoft ranked No. 21 in the 2020 Fortune 500 rankings of the largest United States corporations by total revenue; it was the world's largest software maker by revenue as of 2019. It is one of the Big Five American information technology companies, alongside Alphabet, Amazon, Apple, and Meta. Microsoft was founded by Bill Gates and Paul Allen on April 4, 1975, to develop and sell BASIC interpreters for the Altair 8800. It rose to do ...
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SIMD
Single instruction, multiple data (SIMD) is a type of parallel processing in Flynn's taxonomy. SIMD can be internal (part of the hardware design) and it can be directly accessible through an instruction set architecture (ISA), but it should not be confused with an ISA. SIMD describes computers with multiple processing elements that perform the same operation on multiple data points simultaneously. Such machines exploit data level parallelism, but not concurrency: there are simultaneous (parallel) computations, but each unit performs the exact same instruction at any given moment (just with different data). SIMD is particularly applicable to common tasks such as adjusting the contrast in a digital image or adjusting the volume of digital audio. Most modern CPU designs include SIMD instructions to improve the performance of multimedia use. SIMD has three different subcategories in Flynn's 1972 Taxonomy, one of which is SIMT. SIMT should not be confused with software thr ...
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Video Compression
In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Typically, a device that performs data compression is referred to as an encoder, and one that performs the reversal of the process (decompression) as a decoder. The process of reducing the size of a data file is often referred to as data compression. In the context of data transmission, it is called source coding; encoding done at the source of the data before it is stored or transmitted. Source coding should not be confused with channel coding, for error detection and correction or line coding, the means for mapping data onto a signal. C ...
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SSE2
SSE2 (Streaming SIMD Extensions 2) is one of the Intel SIMD (Single Instruction, Multiple Data) processor supplementary instruction sets first introduced by Intel with the initial version of the Pentium 4 in 2000. It extends the earlier Streaming SIMD Extensions, SSE instruction set, and is intended to fully replace MMX (instruction set), MMX. Intel extended SSE2 to create SSE3 in 2004. SSE2 added 144 new instructions to SSE, which has 70 instructions. Competing chip-maker AMD added support for SSE2 with the introduction of their Opteron and Athlon 64 ranges of x86-64, AMD64 64-bit CPUs in 2003. Features Most of the SSE2 instructions implement the integer vector operations also found in MMX. Instead of the MMX registers they use the XMM registers, which are wider and allow for significant performance improvements in specialized applications. Another advantage of replacing MMX with SSE2 is avoiding the mode switching penalty for issuing x87 instructions present in MMX because it i ...
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