5.3 JPEG2000

Before describing the basic principles of the JPEG2000 standard, it might be useful to understand why we need another standard. Perhaps the most convincing explanation is that, since the introduction of JPEG in the 1980s, too much has changed in the digital image industry. For example, current demands for compressed still images range from web logos of sizes less than 10 Kbytes to high quality scanned images of the order of 5 Gbytes!! [8]. The existing JPEG surely is not optimised to efficiently code such a wide range of images. Moreover, scalability and interoperability requirements of digital imagery in a heterogeneous network of ATM, Internet, mobile etc., make the matter much more complicated.

The JPEG2000 standard is devised with the aim of providing the best quality or performance and capabilities to market evolution that the current JPEG standard fails to cater for. In the mean time it is assumed that Internet, colour facsimile, printing, scanning, digital photography, remote sensing, mobile, medical imagery, digital libraries/archives and e-commerce are among the most immediate demands. Each application area imposes a requirement that JPEG2000 should fulfil. Some of the most important features [9] that this standard aims to deliver are:

Superior low bit rate performance: this standard should offer performance superior to the current standards at low bit rates (e.g. below 0.25 bit per pixel for highly detailed greyscale images). This significantly improved low bit rate performance should be achieved without sacrificing performance on the rest of the rate distortion spectrum. Examples of applications that need this feature include image transmission over networks and remote sensing. This is the highest priority feature.

Continuous tone and bilevel compression: it is desired to have a standard coding system that is capable of compressing both continuous tone and bilevel images [7]. If feasible, the standard should strive to achieve this with similar system resources. The system should compress and decompress images with various dynamic ranges (e.g. 1 bit to 16 bit) for each colour component. Examples of applications that can use this feature include compound documents with images and text, medical images with annotation overlays, graphic and computer generated images with binary and near-to-binary regions, alpha and transparency planes, and facsimile.

Lossless and lossy compression: it is desired to provide lossless compression naturally in the course of progressive decoding (i.e. difference image encoding, or any other technique, which allows for the lossless reconstruction to be valid). Examples of applications that can use this feature include medical images where loss is not always tolerable, image archival pictures where the highest quality is vital for preservation but not necessary for display, network systems that supply devices with different capabilities and resources, and prepress imagery.

Progressive transmission by pixel accuracy and resolution: progressive transmission that allows images to be reconstructed with increasing pixel accuracy or spatial resolution is essential for many applications. This feature allows the reconstruction of images with different resolutions and pixel accuracy, as needed or desired, for different target devices. Examples of applications include web browsing, image archiving and printing.

Region of interest coding: often there are parts of an image that are more important than others. This feature allows a user-defined region of interest (ROI) in the image to be randomly accessed and/or decompressed with less distortion than the rest of the image.

Robustness to bit errors: it is desirable to consider robustness to bit errors while designing the code stream. One application where this is important is wireless communication channels. Portions of the code stream may be more important than others in determining decoded image quality. Proper design of the code stream can aid subsequent error correction systems in alleviating catastrophic decoding failures. Use of error confinement, error concealment, restart capabilities, or source channel coding schemes can help minimise the effects of bit errors.

Open architecture: it is desirable to allow open architecture to optimise the system for different image types and applications. With this feature, the decoder is only required to implement the core tool set and a parser that understands the code stream. If necessary, unknown tools are requested by the decoder and sent from the source.

Protective image security: protection of a digital image can be achieved by means of methods such as: watermarking, labelling, stamping, fingerprinting, encryption, scrambling etc. Watermarking and fingerprinting are invisible marks set inside the image content to pass a protection message to the user. Labelling is already implemented in some imaging formats such as SPIFF, and must be easy to transfer back and forth to the JPEG2000 image file. Stamping is a mark set on top of a displayed image that can only be removed by a specific process. Encryption and scrambling can be applied on the whole image file or limited to part of it (header, directory, image data) to avoid unauthorised use of the image.