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.
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.
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
The outstanding coding performance of H.264 comes with the cost of significantly higher complexity, making it too complex to be applied widely. This work aims at accelerating the H.264 encoder using joint algorithm/code-level optimization techniques so as to make it feasible to perform real-time encoding on a commercial personal computer. We propose a fast inter-mode decision scheme based on spatio-temporal information of neighboring macroblocks for the algorithm-level optimization. We use a commercial profiling tool to identify most time consuming modules and then apply several code-level optimization techniques, including frame-memory rearrangement, single-instruction-multipledata (SIMD) implementations based on the Intel MMX/SSE2 instruction sets. Search mode reordering and early termination for variable block-size motion estimation, are then applied to speed up these time-critical modules. The simulation results show that our proposed joint optimization H.264 encoder achieves a speed-up factor of up to 18 compared to the reference encoder without introducing serious quality degradation.