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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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Motion Estimation
In computer vision and image processing, motion estimation is the process of determining ''motion vectors'' that describe the transformation from one 2D image to another; usually from adjacent video frame, frames in a video sequence. It is an well-posed problem, ill-posed problem as the motion happens in three dimensions (3D) 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 thes ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Theora
Theora is a free lossy video compression format. It was 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 of the Theora video compression format developed by the Xiph.Org Foundation. Theora was derived from the formerly 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 it lacked some of the features present in some of these other codecs. It is comparable in open standards philosophy to the BBC's Dirac codec. Theora was named after Theora Jones, Edison Carter's Controller on the '' Max Headroom'' television program. Technical details Theora is a variable-bitrate, DCT-based video compression scheme. Like most ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 Redundancy (information theory), 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 is 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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Rate–distortion Optimization
Rate-distortion optimization (RDO) is a method of improving video quality in video compression. The name refers to the optimization of the amount of ''distortion'' (loss of video quality) against the amount of data required to encode the video, the ''rate''. While it is primarily used by video encoders, rate-distortion optimization can be used to improve quality in any encoding situation (image, video, audio, or otherwise) where decisions have to be made that affect both file size and quality simultaneously. Background The classical method of making encoding decisions is for the video encoder to choose the result which yields the highest quality output image. However, this has the disadvantage that the choice it makes might require more bits while giving comparatively little quality benefit. One common example of this problem is in motion estimation, and in particular regarding the use of quarter pixel-precision motion estimation. Adding the extra precision to the motion of a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Motion Estimation
In computer vision and image processing, motion estimation is the process of determining ''motion vectors'' that describe the transformation from one 2D image to another; usually from adjacent video frame, frames in a video sequence. It is an well-posed problem, ill-posed problem as the motion happens in three dimensions (3D) 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 thes ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 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). Functionality ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 an 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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Microsoft
Microsoft Corporation is an American multinational corporation and technology company, technology conglomerate headquartered in Redmond, Washington. Founded in 1975, the company became influential in the History of personal computers#The early 1980s and home computers, rise of personal computers through software like Windows, and the company has since expanded to Internet services, cloud computing, video gaming and other fields. Microsoft is the List of the largest software companies, largest software maker, one of the Trillion-dollar company, most valuable public U.S. companies, and one of the List of most valuable brands, most valuable brands globally. Microsoft was founded by Bill Gates and Paul Allen to develop and sell BASIC interpreters for the Altair 8800. It rose to dominate the personal computer operating system market with MS-DOS in the mid-1980s, followed by Windows. During the 41 years from 1980 to 2021 Microsoft released 9 versions of MS-DOS with a median frequen ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
SIMD
Single instruction, multiple data (SIMD) is a type of parallel computer, parallel processing in Flynn's taxonomy. SIMD describes computers with multiple processing elements that perform the same operation on multiple data points simultaneously. 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. Such machines exploit Data parallelism, data level parallelism, but not Concurrent computing, concurrency: there are simultaneous (parallel) computations, but each unit performs exactly the same instruction at any given moment (just with different data). A simple example is to add many pairs of numbers together, all of the SIMD units are performing an addition, but each one has different pairs of values to add. 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 Cen ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 Redundancy (information theory), 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 is 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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
SSE2
SSE2 (Streaming SIMD Extensions 2) is one of the Intel SIMD (Single Instruction, Multiple Data) processor supplementary instruction sets introduced by Intel with the initial version of the Pentium 4 in 2000. SSE2 instructions allow the use of XMM (SIMD) registers on x86 instruction set architecture processors. These registers can load up to 128 bits of data and perform instructions, such as vector addition and multiplication, simultaneously. SSE2 introduced double-precision floating point instructions in addition to the single-precision floating point and integer instructions found in SSE. SSE2 extends earlier SSE instruction set by adding 144 new instructions to the previous 70 instructions. SSE2 intends to fully replace MMX, a SIMD instruction set found on IA-32 architecture processors. Competing chip-maker AMD added support for SSE2 with the introduction of their Opteron and Athlon 64 ranges of AMD64 64-bit CPUs in 2003. SSE2 was extended to create SSE3 in 2004, and e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
