Image Transcoding Research Articles

JPEG column: 82nd JPEG meeting in Lisbon, Portugal

JPEG has been the most common representation format of digital images for more than 25 years. Other image representation formats have been standardised by JPEG committee like JPEG 2000 or more recently JPEG XS. Furthermore, JPEG has been extended with new functionalities like HDR or alpha plane coding with the JPEG XT standard, and more recently with a reference software. Another solutions have been also proposed by different players with limited success. The JPEG committee decided it is the time to create a new working item, named JPEG XL, that aims to develop an image coding standard with increased quality and flexibility combined with a better compression efficiency. The evaluation of the call for proposals responses had already confirmed the industry interest, and development of core experiments has now begun. Several functionalities will be considered, like support for lossless transcoding of images represented with JPEG standard.

Inter-Conversion Matrix for Transcoding Block DCT and DWT-Based Compressed Images

This study derived the inter-conversion matrices, which can be used in heterogeneous image transcoding between the compressed images using different transforms, such as the 8×8 block discrete cosine transform (BDCT) and the one-level discrete wavelet transform (DWT). Basically, to obtain the one-level DWT coefficients from 8×8 BDCT, inverse BDCT should be performed followed by forward DWT, and vice versa. On the other hand, if the proposed interconversion approach is used, only one inter-conversion matrix multiplication makes the corresponding transcoding possible. Both theoretical and experimental analyses showed that the amount of computation of the proposed approach decreases over 20% when the inter-conversion matrices are used under specific conditions.

CCD: A Distributed Publish/Subscribe Framework for Rich Content Formats

In this paper, we propose a content-based publish/subscribe (pub/sub) framework that delivers matching content to subscribers in their desired format. Such a framework enables the pub/sub system to accommodate richer content formats including multimedia publications with image and video content. In our proposed framework, users (consumers) in addition to specifying their information needs (subscription queries), also specify their profile which includes the information about their receiving context which includes characteristics of the device used to receive the content (e.g., resolution of a PDA used by a consumer). The pub/sub system besides being responsible for matching and routing the published content, also becomes responsible for converting the content into the suitable format for each user. Content conversion is achieved through a set of content adaptation operators (e.g., image transcoder, document translator, etc.). We study algorithms for placement of such operators in heterogeneous pub/sub broker overlay in order to minimize the communication and computation resource consumption. Our experimental results show that careful placement of operators in pub/sub overlay network results in significant cost reduction.

A Hadoop-based Multimedia Transcoding System for Processing Social Media in the PaaS Platform of SMCCSE

Previously, we described a social media cloud computing service environment (SMCCSE). This SMCCSE supports the development of social networking services (SNSs) that include audio, image, and video formats. A social media cloud computing PaaS platform, a core component in a SMCCSE, processes large amounts of social media in a parallel and distributed manner for supporting a reliable SNS. Here, we propose a Hadoop-based multimedia system for image and video transcoding processing, necessary functions of our PaaS platform. Our system consists of two modules, including an image transcoding module and a video transcoding module. We also design and implement the system by using a MapReduce framework running on a Hadoop Distributed File System (HDFS) and the media processing libraries Xuggler and JAI. In this way, our system exponentially reduces the encoding time for transcoding large amounts of image and video files into specific formats depending on user-requested options (such as resolution, bit rate, and frame rate). In order to evaluate system performance, we measure the total image and video transcoding time for image and video data sets, respectively, under various experimental conditions. In addition, we compare the video transcoding performance of our cloud-based approach with that of the traditional frame-level parallel processing-based approach. Based on experiments performed on a 28-node cluster, the proposed Hadoop-based multimedia transcoding system delivers excellent speed and quality.

Enhanced JPEG2000 Quality Scalability through Block-Wise Layer Truncation

Quality scalability is an important feature of image and video coding systems. In JPEG2000, quality scalability is achieved through the use of quality layers that are formed in the encoder through rate-distortion optimization techniques. Quality layers provide optimal rate-distortion representations of the image when the codestream is transmitted and/or decoded at layer boundaries. Nonetheless, applications such as interactive image transmission, video streaming, or transcoding demand layer fragmentation. The common approach to truncate layers is to keep the initial prefix of the to-be-truncated layer, which may greatly penalize the quality of decoded images, especially when the layer allocation is inadequate. So far, only one method has been proposed in the literature providing enhanced quality scalability for compressed JPEG2000 imagery. However, that method provides quality scalability at the expense of high computational costs, which prevents its application to the aforementioned applications. This paper introduces a Block-Wise Layer Truncation (BWLT) that, requiring negligible computational costs, enhances the quality scalability of compressed JPEG2000 images. The main insight behind BWLT is to dismantle and reassemble the to-be-fragmented layer by selecting the most relevant codestream segments of codeblocks within that layer. The selection process is conceived from a rate-distortion model that finely estimates rate-distortion contributions of codeblocks. Experimental results suggest that BWLT achieves near-optimal performance even when the codestream contains a single quality layer.

Low-Complexity Transcoding of JPEG Images With Near-Optimal Quality Using a Predictive Quality Factor and Scaling Parameters

A common transcoding operation consists of reducing the file size of a JPEG image to meet bandwidth or device constraints. This can be achieved by reducing its quality factor (QF) or reducing its resolution, or both. In this paper, using the Structural SIMilarity (SSIM) index as the quality metric, we present a system capable of estimating the QF and scaling parameters to achieve optimal quality while meeting a device's constraints. We then propose a novel low-complexity JPEG transcoding system which delivers near-optimal quality. The system is capable of predicting the best combination of QF and scaling parameters for a wide range of device constraints and viewing conditions. Although its computational complexity is an order of magnitude smaller than the system providing optimal quality, the proposed system yields quality results very similar to those of the optimal system.

Efficient Lossless to Lossy Transcoding of JPEG 2000 Codestreams for D-Cinema

This paper presents a method of lossless to lossy transcoding of images that takes advantage of bitplane coding in JPEG 2000. Decoding JPEG 2000 lossless codestreams and subsequently re-encoding them into JPEG 2000 lossy streams consumes lots of computational time. To reduce this time, partial decoding of the lossless codestream is proposed. In addition, by employing a unique rate control, the image quality degradation usually associated with partial decoding is reduced. Experimental results show dramatically reduced computational complexity while the subjective image quality closely approximates that of full lossless decoding.

Arbitrary-ratio image resizing using fast DCT of composite length for DCT-based transcoder

We propose a fast arbitrary-ratio image resizing method for transcoding of the compressed images. The downsizing process in the discrete cosine transform (DCT) domain can be implemented by truncating high-frequency coefficients, whereas the upsizing process is implemented in the DCT domain by padding zero coefficients to the high-frequency part. The proposed method combines a fast inverse and forward DCT of composite length for arbitrary-ratio upsizing or downsizing. According to the resizing ratio, truncating the high-frequency coefficients and padding zeros are appropriately considered by combining the inverse DCT and forward DCT. The proposed method shows a good peak signal-to-noise ratio and less computational complexity compared with the spatial-domain and previous DCT-domain image resizing methods.

A requantization algorithm for the transcoding of JPEG images

Photos from digital camera are mostly lossy compressed in JPEG format, and almost all users do not save or cannot access the original image. Sometimes we need to reduce the size of this JPEG file for saving the disk space or for sending the image to the device with limited bandwidth and/or display size. Since the original image is not available, we need to recompress the already compressed photos. In the existing literature, it is revealed that the direct transcoding (decompressing the JPEG image and then compressing it again with a larger step size) generally results in lower quality images when compared to the one compressed from the original image with the same parameters. This discrepancy is due to the requantization error, and the existing algorithms for more efficient transcoding were focused on finding the requantization step sizes for reducing this error. In this paper, we propose an algorithm that manipulates the requantized DCT coefficients for enhancing the quality of transcoded image, regardless of the choice of requantization step sizes. For this purpose, we first locate the DCT coefficients which have the possibility of causing large requantization errors. But, since the exact requantization error cannot be computed without the original image, we define the error as the discontinuity of pixels around the block boundaries, between the given JPEG image and the targeting one. Then, for the possible variants of these coefficients, the errors are computed and the best combination of coefficients is found. Experimental results show that more coefficients are correctly quantized than the conventional direct requantization, and thus the PSNR as well as the subjective quality is much improved.

Distributing internet services to the network's edge

In the context of industrial information technology, the Internet and World Wide Web increasingly are seen as a solution to the problem of providing "anywhere, anytime" services. In the classical view of an Internet-enabled IT infrastructure, services are requested and consumed by a user (e.g., a human requesting plant production data from his or her desktop) and data are provided by an origin server (e.g., a Web server located in a plant that can authenticate users, implement encryption, serve data, and source multimedia streams). This rather simplistic view works well if the number of users is small, the complexity of services required is modest, and the real-time response requirements are lax. However, it fails to scale when one accounts for the complexities of modern networking: many simultaneous users, potentially operating in multiple languages; many complex data types, including incompatible display formats; many differing schemes for implementing privacy and security through many combinations of authentication and encryption. In this paper we propose an alternative-a client/edge server/origin server architecture that can distribute some complex data processing and device interface tasks to a network edge device, the NetEdge. We show how this device can support services thought to be useful to the industrial environment, such as language translation, image transcoding, access device adaptation, virus scanning, content assembly, local content insertion, and caching. The proposal is a win-win situation for all participants: industrial content providers need maintain only one copy of their content, yet consumers are provided with richer services and device-independent interfaces. Although the services provided define the utility of the product, the heart of the NetEdge is its rule engine. Rules specify which service requests, crossing specified processing points, invoke which service callouts. We explore how a proxylet interface connects the rule engine, through Java and C APIs, to the callout engine. We close with performance measurements of the NetEdge throughput and latency characteristics.

Transcoding: Extending e-business to new environments

The promise of e-business is coming true: both businesses and individuals are using the Web to buy products and services. Both want to extend the reach of e-business to new environments. Customers want to check accounts, access information, and make purchases with their cellular phones, pagers, and personal digital assistants (PDAs). Banks, airlines, and retailers are competing to provide the most ubiquitous, convenient service for their customers. Web applications designed to take advantage of the rich rendering capabilities of advanced desktop browsers on large displays do not generally render effectively on the small screens available on phones and PDAs. Some devices have little or no graphics capability, or they require different markup languages, such as Wireless Markup Language (WML), for text presentation. Transcoding is technology for adapting content to match constraints and preferences associated with specific environments. This paper compares and contrasts different approaches to content adapta tion, including authoring different versions to accommodate different environments, using application server technology such as JavaServer pages™ (JSP™) to create multiple versions of dynamic applications, and dynamically transcoding information generated by a single application. For dynamic transcoding, the paper describes several different transcoding methodologies employed by the IBM WebSphere™ Transcoding Publisher product, including HyperText Markup Language (HTML) simplification, Extensible Markup Language stylesheet selection and application, HTML conversion to WML, WML deck fragmentation, and image transcoding. The paper discusses how to decide whether transcoding should be performed at the content source or in a network intermediary. It also describes a means of identifying the device and network characteristics associated with a request and using that information to decide how to transcode the response. Finally, the paper discusses the need for new networking benchmarks to characterize the server load and performance characteristics for dynamic transcoding.

Dynamic adaptation in an image transcoding proxy for mobile Web browsing

Transcoding proxies are used as intermediaries between generic World Wide Web servers and a variety of client devices in order to adapt to the greatly varying bandwidths of different client communication links and to handle the heterogeneity of possibly small-screened client devices. Such transcoding proxies can adaptively adjust the amount by which a data stream is reduced, using an aggressive lossy compression method (e.g., an image becomes less clear, text is summarized). We present an analytical framework for determining whether to transcode and how much to transcode an image for the two cases of store-and-forward transcoding as well as streamed transcoding. These methods require prediction of transcoding delay, prediction of transcoded image size (in bytes), and estimation of network bandwidth. We discuss methods of adaptation based on fixed quality as well as fixed delay (automated/dynamic transcoding). We conclude with a description of the practical adaptation policies that have been implemented in our adaptive image transcoding proxy.

Transcoding GIF images to JPEG-LS

We investigate transcoding of GIF images to JPEG-LS, the new lossless image compression standard. A straight forward conversion can lead to file sizes that are significantly larger than the size of the corresponding GIF file. We show that suitable reordering of the color table leads to file sizes significantly smaller than those required by the GIF format.

Color Image Transcoding of Lossless Encoder and Standard Lossy Decoder based on JP2K

In JPEG2000 (JP2K) color image system, loss less coding signal is not able to be reconstructed with lossy decoder directly. Then, this report proposes a new transcoding between lossless encoder and standard lossy decoder for color image signals base on JP2K. A proposed encoder is required reversible color transform (RCT) and reversible discrete wavelet transform (RDWT) with compatibility to standard lossy decoder based on JP2K (JP2K lossy decoder). To improve the compatibility, proposed encoder is designed by using Non-scaled RCT and Non-Scaled RDWT with embedding scaling parameter into quantization header. Then, this method can be practical use with JP2K lossy decoder without any change. It also reduces total rounding error and lifting steps. The results show that proposed method can keep lossless coding performance and improve transcoding functionality to JP2K lossy decoder. The quality of transcoding image was achieved to 50.05 dB (PSNR).