High Efficiency Video Coding is the latest in the series of video coding standards developed either by MPEG, or VCEG,
or jointly through a collaboration of the two committees. The first version of HEVC was completed in January 2013, but
was developed without specific requirements for the compression of interlace video content. Rather, the requirements
for the initial version of HEVC targeted the reduction, by 50%, of the bitrate required to delivery progressive video
signals at the same, or nearly the same, visual quality as achieved by current state-of-the-art video codecs. Despite the
lack of formal requirements for the support of interlace scanned content, this first version of HEVC nevertheless
supports interlace video formats but achieves this support in a nominal manner, without the use of specific coding tools.
Interlace formats, however, continue to be the primary format used by broadcasters for the capture and delivery of video
being most recently used exclusively to capture and broadcast the 2012 Summer Olympics for the entire world. This
paper explores the continued importance and relevance of interlace formats for next generation video coding standards,
including HEVC. The in-progress experiments and results of a formal study of HEVC for the coding of interlace content
are presented.
KEYWORDS: Space operations, Image compression, Video coding, Platinum, Video, Inspection, Matrix multiplication, Binary data, Digital image processing, Current controlled current source
Spatial transformations whose kernels employ sinusoidal functions for the decorrelation of signals remain as
fundamental components of image and video coding systems. Practical implementations are designed in fixed precision
for which the most challenging task is to approximate these constants with values that are both efficient in terms of
complexity and accurate with respect to their mathematical definitions. Scaled architectures, for example, as used in the
implementations of the order-8 Discrete Cosine Transform and its corresponding inverse both specified in ISO/IEC
23002-2 (MPEG C Pt. 2), can be utilized to mitigate the complexity of these approximations. That is, the
implementation of the transform can be designed such that it is completed in two stages: 1) the main transform matrix in
which the sinusoidal constants are roughly approximated, and 2) a separate scaling stage to further refine the
approximations. This paper describes a methodology termed the Common Factor Method, for finding fixed-point
approximations of such irrational values suitable for use in scaled architectures. The order-16 Discrete Cosine
Transform provides a framework in which to demonstrate the methodology, but the methodology itself can be employed
to design fixed-point implementations of other linear transformations.
Fixed-point implementations of transforms such as the Discrete Cosine Transform (DCT) remain as fundamental
building blocks of state-of-the-art video coding technologies. Recently, the 16x16 DCT has received focus as a
transform suitable for the high efficiency video coding project currently underway in the Joint Collaboration Team - Video Coding. By its definition, the 16x16 DCT is inherently more complex than transforms of traditional sizes such as
4x4 or 8x8 DCTs. However, scaled architectures such as the one employed in the design of the 8x8 DCTs specified in
ISO/IEC 23002-2 can also be utilized to mitigate the complexity of fixed-point approximations of higher-order
transforms such as the 16x16 DCT. This paper demonstrates the application of the Common Factor method to design
two scaled implementations of the 16x16 DCT. One implementation can be characterized by its exceptionally low
complexity, while the other can be characterized by its relatively high precision. We review the Common Factor method
as a method to arrive at fixed-point implementations that are optimized in terms of complexity and precision for such
high performance transforms.
The Joint Photographic Experts Group (JPEG) baseline standard remains a popular and pervasive standard for
continuous tone, still image coding. The "J" in JPEG acknowledges its two main parent organizations, ISO
(International Organization for Standardization) and the ITU-T (International Telecommunications Union -
Telecommunication). Notwithstanding their joint efforts, both groups have subsequently (and separately) standardized
many improvements for still image coding. Recently, the ITU-T Study Group 16 completed the standardization for a
new entropy coder - called the Q15-coder, whose statistical model is from the original JPEG-1 standard. This new
standard, ITU-T Rec. T.851, can be used in lieu of the traditional Huffman (a form of variable length coding) entropy
coder, and complements the QM arithmetic coder, both originally standardized in JPEG as ITU-T T.81 | ISO/IEC
10918:1. In contrast to Huffman entropy coding, arithmetic coding makes no assumptions about an image's statistics,
but rather responds in real time. This paper will present a tutorial on arithmetic coding, provide a history of arithmetic
coding in JPEG, share the motivation for T.851, outline its changes, and provide comparison results with both the
baseline Huffman and the original QM-coder entropy coders. It will conclude with suggestions for future work.
KEYWORDS: CMYK color model, Data modeling, Data conversion, Printing, Image compression, Data centers, Space operations, Mathematical modeling, RGB color model, Digital image processing
A new technique is described for color conversions of JPEG images. For each input block of each
component, the conversion for the 63 AC coefficients is processed in the transform domain instead of the
spatial domain. Only the DC coefficients for each input block of the color components are transformed to
the spatial domain and then processed through the traditional lookup table to create color-converted output
DC coefficients for each block. Given each converted DC value for each block, the remaining 63 AC
coefficients are then converted directly in the transform domain via scaling functions that are accessed via a
table as a function of only the DC term. For n-dimensional color space to m-dimensional color space
conversion, n component blocks create m component blocks. An IDCT can then be applied to the m
component blocks to create spatial domain data or these output blocks can be quantized and entropy
encoded to create JPEG compressed data in the m-dimensional color space.
This paper describes fixed-point design methodologies and several resulting implementations of the Inverse
Discrete Cosine Transform (IDCT) contributed by the authors to MPEG's work on defining the new 8x8 fixed
point IDCT standard - ISO/IEC 23002-2. The algorithm currently specified in the Final Committee Draft (FCD)
of this standard is also described herein.
This paper analyzes the drift phenomenon that occurs between video encoders and decoders that employ different
implementations of the Inverse Discrete Cosine Transform (IDCT). Our methodology utilizes MPEG-2, MPEG-4
Part 2, and H.263 encoders and decoders to measure drift occurring at low QP values for CIF resolution video
sequences. Our analysis is conducted as part of the effort to define specific implementations for the emerging ISO/IEC
23002-2 Fixed-Point 8x8 IDCT and DCT standard. Various IDCT implementations submitted as proposals for the new
standard are used to analyze drift. Each of these implementations complies with both the IEEE Standard 1180 and the
new MPEG IDCT precision specification ISO/IEC 23002-1. Reference implementations of the IDCT/DCT, and
implementations from well-known video encoders/decoders are also employed. Our results indicate that drift is
eliminated entirely only when the implementations of the IDCT in both the encoder and decoder match exactly. In this
case, the precision of the IDCT has no influence on drift. In cases where the implementations are not identical, then the
use of a highly precise IDCT in the decoder will reduce drift in the reconstructed video sequence only to the extent that
the IDCT used in the encoder is also precise.
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