Charilaos Christopoulos

The JPEG2000 still image coding system: an overview

With the increasing use of multimedia technologies, image compression requires higher performance as well as new features. To address this need in the specific area of still image encoding, a new standard is currently being developed, the JPEG2000. It is not only intended to provide rate-distortion and subjective image quality performance superior to existing standards, but also to provide features and functionalities that current standards can either not address efficiently or in many cases cannot address at all. Lossless and lossy compression, embedded lossy to lossless coding, progressive transmission by pixel accuracy and by resolution, robustness to the presence of bit-errors and region-of-interest coding, are some representative features. It is interesting to note that JPEG2000 is being designed to address the requirements of a diversity of applications, e.g. Internet, color facsimile, printing, scanning, digital photography, remote sensing, mobile applications, medical imagery, digital library and E-commerce.

The JPEG 2000 still image compression standard

One of the aims of the standardization committee has been the development of Part I, which could be used on a royalty- and fee-free basis. This is important for the standard to become widely accepted. The standardization process, which is coordinated by the JTCI/SC29/WG1 of the ISO/IEC has already produced the international standard (IS) for Part I. In this article the structure of Part I of the JPFG 2000 standard is presented and performance comparisons with established standards are reported. This article is intended to serve as a tutorial for the JPEG 2000 standard. The main application areas and their requirements are given. The architecture of the standard follows with the description of the tiling, multicomponent transformations, wavelet transforms, quantization and entropy coding. Some of the most significant features of the standard are presented, such as region-of-interest coding, scalability, visual weighting, error resilience and file format aspects. Finally, some comparative results are reported and the future parts of the standard are discussed.

Video transcoding architectures and techniques: an overview

Throughout this article, we concentrate on the transcoding of block-based video coding schemes that use hybrid discrete cosine transform (DCT) and motion compensation (MC). In such schemes, the frames of the video sequence are divided into macroblocks (MBs), where each MB typically consists of a luminance block (e.g., of size 16 /spl times/ 16, or alternatively, four 8 /spl times/ 8 blocks) along with corresponding chrominance blocks (e.g., 8 /spl times/ 8 Cb and 8 /spl times/ 8 Cr). This article emphasizes the processing that is done on the luminance components of the video. In general, the chrominance components can be handled similarly and will not be discussed in this article. We first provide an overview of the techniques used for bit-rate reduction and the corresponding architectures that have been proposed. Then, we describe the advances regarding spatial and temporal resolution reduction techniques and architectures. Additionally, an overview of error resilient transcoding is also provided, as well as a discussion of scalable coding techniques and how they relate to video transcoding. Finally, the article ends with concluding remarks, including pointers to other works on video transcoding that have not been covered in this article, as well as some future directions.

Efficient methods for encoding regions of interest in the upcoming JPEG2000 still image coding standard

The general method for generating the regions of interest (ROI) mask needed for encoding ROI in the upcoming JPEG2000 still image coding standard is presented. A simple method for the generation of the ROI mask for rectangular-shaped ROI is then proposed. Finally, to simplify the decoder when dealing with arbitrary shaped ROIs, a method for ROI coding that does not require any shape information to be transmitted to the decoder is described. A small coding penalty is associated with this method, while it makes it possible to have arbitrarily shaped ROI without the need of shape information and ROI mask generation at the decoder. The proposed methods have been included in the Final Committee Draft of JPEG2000 Part 1.

JPEG2000: the upcoming still image compression standard

With the increasing use of multimedia technologies, image compression requires higher performance as well as new features. To address this need in the specific area of still image encoding, a new standard is currently being developed, the JPEG2000. It is not only intended to provide rate-distortion and subjective image quality performance superior to existing standards, but also to provide functionality that current standards can either not address efficiently or not address at all.

Transcoder architectures for video coding

This paper discusses the problem of transcoding H.263-based video streams. Two different models for transcoding are examined, rate reduction and resolution reduction. Results show that the computational complexity of the basic transcoding model can be reduced for each model by, on average, 39% and 23% without significant lose in quality. Comparisons with the scaleable coding model are also shown.

JPEG 2000 still image coding versus other standards

JPEG 2000, the new ISO/ITU-T standard for still image coding, is about to be finished. Other new standards have been recently introduced, namely JPEG-LS and MPEG-4 VTC. This paper puts into perspective the performance of these by evaluating JPEG 2000 versus JPEG-LS and MPEG-4 VTC, as well as the older but widely used JPEG. The study concentrates on compression efficiency, although complexity and set of supported functionalities are also evaluated. Lossless compression efficiency as well as the lossy rate-distortion behavior is discussed. The principles behind each algorithm are briefly described and an outlook on the future of image coding is given. The results show that the choice of the “best” standard depends strongly on the application at hand.

Lossless region of interest coding

In a method and a device for transmission of S+P transform coded digitized images a mask is calculated by means of which a region of interest (ROI) can be transmitted lossless whereby the ROI can be transmitted and received lossless and still maintaining a good compression ratio for the image as a whole. This is possible since no or very few bits can be used for the remaining part of the image. The calculated mask can also be used for transmitting the coefficients needed for a lossless region of interest during any stage of the transmission.

Region of interest coding in JPEG 2000

This paper describes the functionality in the JPEG 2000 Part 1 standard, for encoding images with predefined regions of interest (ROI) of arbitrary shape. The method described is called the Maxshift method. This method is based on scaling of the wavelet coefficients after the wavelet transformation and quantization. By sufficiently scaling the wavelet coefficients used to reconstruct the ROI, all the information pertaining to the ROI is placed before the information pertaining to the rest of the image (background), in the codestream. By varying the quantization of the image and by truncation of the codestream, different quality for the ROI and for the background can be obtained. A description is also given of how the wavelet coefficients that are used to reconstruct the ROI (ROI mask) can be found. Since the decoder uses only the number of significant bitplanes for each wavelet coefficient to determine whether it should be scaled back, an arbitrary set of wavelet coefficients can be scaled on the encoder side. This means that there is no need to encode or send the shape of the ROI. This paper also describes how this can be used to further enhance the ROI functionality. The results in this paper show that the Maxshift method can be used to greatly increase the compression efficiency by lowering the quality of the background and that it also makes it possible to receive the ROI before the background, when transmitting the image.

An embedded DCT-based still image coding algorithm

An embedded DCT-based image coding algorithm is described. The decoder can cut the bitstream at any point and therefore reconstruct an image at lower rate. The quality of the reconstructed image at this lower rate would be the same as if the image was coded directly at that rate. The algorithm outperforms any other DCT-based coders published in the literature, including the JPEG algorithm. Moreover, our DCT-based embedded image coder gives results close to the best wavelet-based coders. The algorithm is very useful in various applications, like WWW, fast browsing of databases, etc.An embedded discrete cosine transform-based (DCT-based) image coding algorithm is described. The algorithm outperforms other DCT-based coders published in the literature, including the Joint Photographers Expert Group (JPEG) algorithm.