Joint Photographic Experts Group (JPEG) XS is a new International Standard from the JPEG Committee (formally known as ISO/International Electrotechnical Commission (IEC) JTC1/SC29/WG1). It defines an interoperable, visually lossless low-latency lightweight image coding that can be used for mezzanine compression within any AV market. Among the targeted use cases, one can cite video transport over professional video links (serial digital interface (SDI), internet protocol (IP), and Ethernet), real-time video storage, memory buffers, omnidirectional video capture and rendering, and sensor compression (for example, in cameras and the automotive industry). The core coding system is composed of an optional color transform, a wavelet transform, and a novel entropy encoder, processing groups of coefficients by coding their magnitude level and packing the magnitude refinement. Such a design allows for visually transparent quality at moderate compression ratios, scalable end-to-end latency that ranges from less than one line to a maximum of 32 lines of the image, and a low-complexity real-time implementation in application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), central processing unit (CPU), and graphics processing unit (GPU). This article details the key features of this new standard and the profiles and formats that have been defined so far for the various applications. It also gives a technical description of the core coding system. Finally, the latest performance evaluation results of recent implementations of the standard are presented, followed by the current status of the ongoing standardization process and future milestones.

While traditional image compression algorithms take a full three-component color representation of an image as input, capturing of such images is done in many applications with Bayer CFA pattern sensors that provide only a single color information per sensor element and position. In order to avoid additional complexity at the encoder side, such CFA pattern images can be compressed directly without prior conversion to a full color image. In this paper, we describe a recent activity of the JPEG committee (ISO SC 29 WG 1) to develop such a compression algorithm in the framework of JPEG XS. It turns out that it is important to understand the "development process" from CFA patterns to full color images in order to optimize the image quality of such a compression algorithm, which we will also describe shortly. We introduce (1) a novel decorrelation step upfront processing (the so-called Star-Tetrix transform), along with (2) a pre-emphasis function to improve the compression efficiency of the subsequent compression algorithm (here, JPEG XS). Our experiments clearly indicate a gain over a RGB compression workflow in terms of complexity and quality (between 1.5dB and more than 4dB depending on the target bitrate). A comparison is also made with other state-of-the-art CFA compression techniques.

JPEG XS is a new standard for low-latency and low-complexity coding designed by the JPEG committee. Unlike former developments, optimal rate distortion performance is only a secondary goal; the focus of JPEG~XS is to enable cost-efficient, easy to parallelize implementations suitable for FPGAs or GPUs. In this article, we shed some light on the entropy coding back-end of JPEG~XS and introduce modifications of the entropy coding stage currently under discussion that improve objective and subjective quality of the compressed images without compromising the parallelism of the original algorithm.

With the emergence of UHD video, reference frame buffers (FBs) inside HEVC-like encoder and decoder chips have to sustain huge bandwidth. The power consumption due to the accesses to these off-chip memories accounts for a significant share of the codec's total consumption. This paper describes a JPEG XS-based frame buffer compression solution intended to decrease the FB's bandwidth, making HEVC more suitable for use in power-aware applications. As opposed to previous works, our solution compresses large picture areas (ranging from a CTU to a frame stripe) independently and is suitable for use in several data reuse strategies. According to experimental results, this work provides significant off-chip bandwidth and memory size reduction (DRR) at the cost of a slight rate increase. In particular, at low rates and if FBC is applied at HEVC encoder only, the DRR is as high as 83.3% with a rate increase and quality drop on average.

The JPEG committee (formally, ISO SC29 WG1) is currently standardizing a lightweight mezzanine codec for video over IP transport under the name JPEG XS. A particular challenging design constraint of this codec is multi-generation robustness, that is the necessity to minimize the error built-up under multiple re-compression cycles. In this paper, we discuss the sources of such errors, how they are avoided in the JPEG XS design and compare the multi-generation robustness of JPEG XS with that of other codecs.

In this paper, we address the issues of analyzing and classifying JPEG 2000 code-streams. An original representation, called integral volume, is first proposed to compute local image features progressively from the compressed code-stream, on any spatial image area, regardless of the code-blocks borders. Then, a JPEG 2000 classifier is presented that uses integral volumes to learn an ensemble of randomized trees. Several classification tasks are performed on various JPEG 2000 image databases and results are in the same range as the ones obtained in the literature with noncompressed versions of these databases. Finally, a cascade of such classifiers is considered, in order to specifically address the image retrieval issue, i.e., bi-class problems characterized by a highly skewed distribution. An efficient way to learn and optimize such cascade is proposed. We show that staying in a JPEG 2000 framework, initially seen as a constraint to avoid heavy decoding operations, is actually an advantage as it can benefit from the multiresolution and multilayer paradigms inherently present in this compression standard. In particular, unlike other existing cascaded retrieval systems, the features used along our cascade are increasingly discriminant and lead therefore to a better tradeoff of complexity versus performance.

This paper considers the issues of scheduling and caching JPEG2000 data in client/server interactive browsing applications, under memory and channel bandwidth constraints. It analyzes how the conveyed data have to be selected at the server and managed within the client cache so as to maximize the reactivity of the browsing application. Formally, to render the dynamic nature of the browsing session, we assume the existence of a reaction model that defines when the user launches a novel command as a function of the image quality displayed at the client. As a main outcome, our work demonstrates that, due to the latency inherent to client/server exchanges, a priori expectation about future navigation commands may help to improve the overall reactivity of the system. In our study, the browsing session is defined by the evolution of a rectangular window of interest (WoI) along the time. At any given time, the WoI defines the position and the resolution of the image data to display at the client. The expectation about future navigation commands is then formalized based on a stochastic navigation model, which defines the probability that a given WoI is requested next, knowing previous WoI requests. Based on that knowledge, several scheduling scenarios are considered. The first scenario is conventional and transmits all the data corresponding to the current WoI before prefetching the most promising data outside the current WoI. Alternative scenarios are then proposed to anticipate prefetching, by scheduling data expected to be requested in the future before all the current WoI data have been sent out. Our results demonstrate that, for predictable navigation commands, anticipated prefetching improves the overall reactivity of the system by up to 30% compared to the conventional scheduling approach. They also reveal that an accurate knowledge of the reaction model is not required to get these significant improvements.

This paper considers the remote interactive browsing of large JPEG2000 images. In contrast with previous contributions, we focus on the dynamic nature of the system. Practically, we study the conditions under which a priori knowledge about the user behavior may help to improve the browsing system reactivity, when combined with appropriate pre-fetching mechanisms. In particular, our simulations show that, due to the latency inherent to client/server exchanges, a benefit can be drawn by scheduling future window of interest (WoI) data before all current WoI data have been sent to the client. They also reveal that an accurate knowledge of the user behavior is not necessary to get important improvements over conventional scheduling approaches.

<?Pub _touchup WordspNominal="1.6" WordspMinimum="1.3" WordspMaximum="2.9"?>The image compression standard JPEG 2000 proposes a large set of features that is useful for today's multimedia applications. Unfortunately, it is much more complex than older standards. Real-time applications, such as digital cinema, require a specific, secure, and scalable hardware implementation. In this paper, a decoding scheme is proposed with two main characteristics. First, the complete scheme takes place in a field-programmable gate array without accessing any external memory, allowing integration in a <?Pub /_touchup?>secured system. Second, a customizable level of parallelization allows to satisfy a broad range of constraints, depending on the signal resolution. The resulting architecture is therefore ready to meet upcoming digital cinema specifications.

Remote access to large scale images arouses a growing interest in fields such as medical imagery or remote sensing. This raises the need for algorithms guaranteeing navigation smoothness while minimizing the network resources used. In this paper, we present a model taking advantage of the JPEG 2000 scalability combined with a prefetching policy. The model uses the last user action to efficiently manage the cache and to prefetch the most probable data to be used next. Three different network configurations are considered. In each case, comparison with two more classic policies shows the improvement brought by our approach.