JPEG XR, a new international standard for image coding, was approved as ITU-T Recommendation T.832 in
March 2009, and as ISO/IEC international standard 29199-2 in July 2009. JPEG XR was designed based on Microsoft
coding technology known as HD Photo. Since JPEG XR is an emerging new specification, exploration of advanced
encoding techniques for JPEG XR is an important area of study. In order to advance understanding of JPEG XR and its
capabilities, the development of enhanced encoding techniques for optimization of encoded JPEG XR perceptual image
quality is particularly valuable. This paper presents techniques and results focusing on exploring the capabilities of the
spatially adaptive quantization syntax of the emerging JPEG XR standard.
This paper explores several encoder-side techniques aimed at improving the compression performance of encoding for
the draft JPEG XR standard. Though the syntax and decoding process are fixed by the standard, significant variation in
encoder design and some variation in decoder design are possible. For a variety of selected quality metrics, the paper
discusses techniques for achieving better compression performance according to each metric. As a basic reference
encoder and decoder for the discussion and modifications, the publically available Microsoft HD Photo DPK (Device
Porting Kit) 1.0, on which the draft JPEG XR standard was based, was used. The quality metrics considered include
simple mathematical objective metrics (PSNR and L∞) as well as pseudo-perceptual metrics (single-scale and multi-scale
MSSIM).
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.
A new technique for film grain noise extraction, modeling and synthesis is proposed and applied to the coding
of high definition video in this work. The film grain noise is viewed as a part of artistic presentation by people
in the movie industry. On one hand, since the film grain noise can boost the natural appearance of pictures
in high definition video, it should be preserved in high-fidelity video processing systems. On the other hand,
video coding with film grain noise is expensive. It is desirable to extract film grain noise from the input video
as a pre-processing step at the encoder and re-synthesize the film grain noise and add it back to the decoded
video as a post-processing step at the decoder. Under this framework, the coding gain of the denoised video
is higher while the quality of the final reconstructed video can still be well preserved. Following this idea, we
present a method to remove film grain noise from image/video without distorting its original content. Besides, we
describe a parametric model containing a small set of parameters to represent the extracted film grain noise. The
proposed model generates the film grain noise that is close to the real one in terms of power spectral density and
cross-channel spectral correlation. Experimental results are shown to demonstrate the efficiency of the proposed
scheme.
This paper studies the rate-distortion performance of symmetric scalar quantizers to extend previous work published by the first author. We first provide a theoretical analysis of dead-zone plus uniform threshold quantization (DZ+UTQ) for nearly-uniform-reconstruction quantization (NURQ). The quantization performance is particularly investigated for Generalized Gaussian (such as Laplacian and Gaussian) sources using the squared-error distortion measure. According to the analysis, we note that the rate-distortion optimized quantizer is DZ+UTQ with NURQ for Laplacian sources, and is very similar to a DZ+UTQ for a uniform reconstruction quantizer (URQ). We further provide theoretical analysis of rate-distortion constrained DZ+UTQ with NURQ and URQ to cover other Generalized Gaussian sources and give the rate-distortion performance comparison theoretically between NURQ and URQ for DZ+UTQ. We conclude that a URQ is a near-optimal reconstruction rule for many sources, and that a DZ+UTQ classification rule is an effective classifier for it. URQ can be considered as a sub-optimal case of NURQ; the advantage of URQ being its simpler reconstruction rule. Based on the theoretical findings, a new DZ+UTQ quantization rounding technique for URQ is developed and integrated into recent H.264/AVC reference software to improve its encoding performance. Up to 1.0 dB performance improvement is observed, particularly in the very high bit rate range.
KEYWORDS: Video, Video coding, Scalable video coding, Video compression, Computer programming, Video processing, Image processing, Composites, Image compression, Standards development
The amount of data that has to be stored and transmitted for stereo-view video applications can be double of conventional mono-view video applications if a mono-view video coding method is applied directly. Although not designed for stereo-view video coding, the H.264 coding tools can be arranged to take advantage of the correlations between the pair of views of a stereo-view video, and provide very reliable and efficient compression performance as well as stereo/mono-view scalability. This paper introduces methods for coding stereo-view video sequences efficiently using the H.264 coding tools, such as the interlace-coding tools and the sub-sequence coding concept. With the help of the stereo video Supplemental Enhancement Information (SEI) message defined in H.264 Fidelity Range Extensions (FRExt), a decoder can easily synchronize the views, and a streaming server or a decoder can easily detect the scalability of a coded stereo video bitstream. Coding performances are shown in the paper for Main and Baseline profiles using both scalable and non-scalable coding options. The scalable coding options that can be signaled by the H.264 SEI messages could have coding performance similar to or better than that of proprietary system configurations for non-scalable coding.
Predictive motion estimation techniques have become widely used in video coding systems due to their reasonable coding performance and low computational requirement compared to the brute force full search method. However, most existing predictive motion estimation algorithms focus mainly on local motions and consider motion predictions from only neighboring image blocks (either spatially or temporally). In this paper, a reliable global motion predictor or GMP is introduced to improve predictive motion estimation for sequences with fast camera motions. A simple global motion model is applied for global motion estimation. The derived global motion vector for each macroblock is then used as the GMP during the predictive motion estimation for all possible block modes or types, together with up to 8 local motion predictors for P frame motion estimation and up to 12 local motion predictors for B frame motion estimation. The comparison between the coding performance with and without GMP shows very significant differences; roughly 1-2 dB’s improvement is achieved by GMP for sequences with very fast camera motions. The computational overhead for GMP is very small, less than 2% of the total computation cycles in our H.264 encoder.
In this paper, we demonstrate the performance of a lossless video-coding algorithm based on the existing H.26L test model. The lossless coding algorithm is formed by simply skipping the transform and quantization operations in H.26L; therefore, the main elements in this lossless coding algorithm are motion compensation, Intra prediction, and entropy coding tools of H.26L. It has been demonstrated that H.26L has significant good performance at both low bit rates and high bit rates for lossy video coding. Here we further demonstrate the competitive performance of lossless video coding using H.26L tools. The H.26L lossless video coding results are compared to those of Motion JPEG2000. When Inter coding tool is applied, H.26L provides on average 32% bit reduction comparing to Motion JPEG2000. We evaluate the performances of H.26L Intra and Inter coding separately. The motion compensation techniques adopted in H.26L proves to be also effective for lossless coding. There is roughly 40% bit saving when Inter frame coding is turned on. The performance of Intra prediction of H.26L for lossless coding is not as impressive as that of the H.26L motion compensation; the bitrate increases on average by 19% comparing to that of Motion JPEG2000, which also uses only Intra coding tools. The results indicate that H.26L Intra coding could further be improved. Possible improvements for H.26L lossless video coding are suggested in the paper.
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