This paper discusses cascaded multiple encoding/decoding cycles and their effect on image quality for lossy image
coding designs. Cascaded multiple encoding/decoding is an important operating scenario in professional editing
industries. In such scenarios, it is common for a single image to be edited by several people while the image is
compressed between editors for transit and archival. In these cases, it is important that decoding followed by re-encoding
introduce minimal (or no) distortion across generations. A significant number of potential sources of distortion
introduction exist in a cascade of decoding and re-encoding, especially if such processes as conversion between RGB
and YUV color representations, 4:2:0 resampling, etc., are considered (and operations like spatial shifting, resizing, and
changes of the quantization process or coding format). This paper highlights various aspects of distortion introduced by
decoding and re-encoding, and remarks on the impact of these issues in the context of three still-image coding designs:
JPEG, JPEG 2000, and JPEG XR. JPEG XR is a draft standard under development in the JPEG committee based on
Microsoft technology known as HD Photo. The paper focuses particularly on the JPEG XR technology, and suggests
that the design of the draft JPEG XR standard has several quite good characteristics in regard to re-encoding robustness.
KEYWORDS: High dynamic range imaging, Computer programming, Image compression, Data conversion, RGB color model, Standards development, Image processing, Erbium, Range imaging, Signal processing
High Dynamic Range (HDR) imaging support is one of the major features for the emerging draft JPEG XR standard.
JPEG XR is being standardized within the JPEG committee based on Microsoft technology known as HD Photo.
JPEG XR / HD Photo is primarily an integer-based coding technology design, accepting integer valued samples at the
encoder and producing integer valued samples at the decoder, with internal processing entirely in the integer space. Yet,
it can support compression of multiple HDR formats, including 16- and 32-bit float, 16-bit and 32-bit signed and
unsigned integer, and RGBE. Further, JPEG XR can enable lossless compression of some HDR formats such as 16-bit
signed and unsigned, 16-bit float and RGBE. This paper describes how HDR formats are handled in JPEG XR. It
examines in depth how these various HDR formats are converted to and from integer valued samples within the
JPEG XR codec, and the internal processing of these HDR formats. This paper describes how JPEG XR provides
flexible ways to compress HDR formats within the same codec framework as integer-valued formats, while maintaining
from the high compression efficiency and low computational complexity.
JPEG XR is a draft international standard undergoing standardization within the JPEG committee, based on a Microsoft
technology known as HD Photo. One of the key innovations in the draft JPEG XR standard is its integer-reversible
hierarchical lapped transform. The transform can provide both bit-exact lossless and lossy compression in the same
signal flow path. The transform requires only a small memory footprint while providing the compression benefits of a
larger block transform. The hierarchical nature of the transform naturally provides three levels of multi-resolution signal
representation. Its small dynamic range expansion, use of only integer arithmetic and its amenability to parallelized
implementation lead to reduced computational complexity. This paper provides an overview of the key ideas behind the
transform design in JPEG XR, and describes how the transform is constructed from simple building blocks.
KEYWORDS: Image compression, Quantization, Image quality, Computer programming, High dynamic range imaging, RGB color model, Digital photography, Digital imaging, Raster graphics, Image resolution
This paper introduces the HD Photo coding technology developed by Microsoft Corporation. The storage format for this
technology is now under consideration in the ITU-T/ISO/IEC JPEG committee as a candidate for standardization under
the name JPEG XR. The technology was developed to address end-to-end digital imaging application requirements,
particularly including the needs of digital photography. HD Photo includes features such as good compression capability,
high dynamic range support, high image quality capability, lossless coding support, full-format 4:4:4 color sampling,
simple thumbnail extraction, embedded bitstream scalability of resolution and fidelity, and degradation-free compressed domain
support of key manipulations such as cropping, flipping and rotation. HD Photo has been designed to optimize
image quality and compression efficiency while also enabling low-complexity encoding and decoding implementations.
To ensure low complexity for implementations, the design features have been incorporated in a way that not only
minimizes the computational requirements of the individual components (including consideration of such aspects as
memory footprint, cache effects, and parallelization opportunities) but results in a self-consistent design that maximizes
the commonality of functional processing components.
A pre/post-filtering framework for DCT image coding has been proposed recently. Together withWiener filtering
technique, the new framework has been investigated for error resilient image coding. In this paper, after a review
of existing methods, we analyze the limitation associated with one of the current design criteria, the reconstruction
gain, and propose an alternative that offers better control of the error distribution, thereby improving the visual
quality of the reconstructed image in the presence of transmission error. The performance of the proposed scheme
is demonstrated through various multiple description coding (MDC) simulations.
KEYWORDS: Video coding, Video compression, Motion estimation, Video, Video processing, Computer programming, Signal processing, Multimedia, Quantization, Internet
Standard video compression algorithms share one common coding framework based on the hybrid block-based motion-compensated DCT structure. Recently, video compression at low bit-rates has become the focus of research in the signal processing community due to the expanding applications in video conferencing, video over telephone lines, streaming video over the Internet, multimedia and wireless video communications. Unfortunately, in these situations, the notorious blocking artifacts resulting from block DCT and block-based motion estimation/compensation set a severe limit on the achievable bit-rate with acceptable quality. To avoid blocking artifacts and to improve video coding efficiency, this paper presents a novel video compression algorithm based on the lapped transform and overlapping block motion estimation/compensation. Our long-term focus is to develop a complete integrated framework for lapped-transform-based video coding, ranging from theory, design, fast implementations, to practically desirable features for video streaming and delivery over communication networks. In this paper, we are mainly concerned with fundamental theoretical issues. The goals of the proposed video coding technique are to eliminate blocking artifacts and to improve coding efficiency while maintaining a minimal complexity overhead and retaining the flexibility that block-based methods possess. Preliminary coding results confirm the validity of the proposed theory.
It has been well established that state-of-the-art wavelet image coders outperform block transform image coders in the rate-distortion (R-D) sense by a wide margin. Wavelet-based JPEG2000 is emerging as the new high-performance international standard for still image compression. An often asked question is: how much better are wavelets comparing to block transforms in image coding? A notable observation is that each block transform coefficient is highly correlated with its neighbors within the same block as well as its neighbors within the same subband. Current block transform coders such as JPEG suffer from poor context modeling and fail to take full advantage of inter-block correlation in both space and frequency sense. This paper presents a simple, fast and efficient adaptive block transform image coding algorithm based on a combination of pre-filtering, post-filtering, and high-order space-frequency context modeling of block transform coefficients. Despite the simplicity constraints, coding results show that the proposed codec achieves competitive R-D performance comparing to the best wavelet codecs.
This paper introduces a fast block-based motion estimation algorithm based on matching projections. The idea is simple: blocks cannot match well if their corresponding 1D projections do not match well. We can take advantage of this observation to translate the expensive 2D block matching problem to a simpler 1D matching one by quickly eliminating a majority of matching candidates. Our novel motion estimation algorithm offers computational scalability through a single parameter and global optimum can still be achieved. Moreover, an efficient implementation to compute projections and to buffer recyclable data is also presented. Experiments show that the proposed algorithm is several times faster than the exhaustive search algorithm with nearly identical prediction performance. With the proposed BME method, high-performance real-time all- software video encoding starts to become practical for reasonable video sizes.
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