Martin Boliek

An overview of JPEG-2000

JPEG-2000 is an emerging standard for still image compression. This paper provides a brief history of the JPEG-2000 standardization process, an overview of the standard, and some description of the capabilities provided by the standard. Part I of the JPEG-2000 standard specifies the minimum compliant decoder, while Part II describes optional, value-added extensions. Although the standard specifies only the decoder and bitstream syntax, in this paper we describe JPEG-2000 from the point of view of encoding. We take this approach, as we believe it is more amenable to a compact description more easily understood by most readers.

Decoding compression with reversible embedded wavelets (CREW) codestreams

As the applications of digital imagery expand in resolution and pixel fidelity there is a greater need for more efficient compression and extraction of images and subimages. No longer is it sufficient to compress and decompress an image for a specific target device. The ability to handle many types of image data, extract images at different resolutions and quality, lossless and lossy, zoom and pan, and extract regions-of-interest are the new measures of image compression system performance. Compression with reversible embedded wavelets (CREW) is a high-quality image compression system that is progressive from high compression to lossless, and pyramidal in resolution. CREW supports regions-of-interest, and multiple image types, such as bi-level and continuous-tone. This paper describes the CREW system and format, shows how the correct data can be quickly extracted from a CREW file to support a variety of target devices, describes the mechanisms needed for panning, zooming, and fixed-size compression, and explains the superior performance on bi-level and graphic images.

Next Generation Image Compression And Manipulation Using CREW

As the applications of digital imagery expand in resolution and pixel fidelity there is a greater need for more efficient compression and extraction of images and sub-images. No longer is it sufficient to compress and decompress an image for a specific target device. The ability to handle many types of image data, extract images at different resolutions and quality, zoom and pan, and to extract regions-of-interest are the new measures of image compression systems. CREW (compression with reversible embedded wavelets) is a high quality image compression system that is progressive from high compression to lossless, pyramidal, and supports regions-of-interest and multiple image types. This paper describes the CREW system and format, shows how the correct data can be quickly extracted from a CREW file to support a variety of target devices, describes the mechanisms needed for panning, zooming, and fixed-size compression, and explains the superior performance on bi-level and graphic images.As the applications of digital imagery expand in resolution and pixel fidelity there is a greater need for more efficient compression and extraction of images and sub-images. No longer is it sufficient to compress and decompress an image for a specific target device. The ability to handle many types of image data, extract images at different resolutions and quality, zoom and pan, and to extract regions-of-interest are the new measures of image compression systems. CREW (compression with reversible embedded wavelets) is a high quality image compression system that is progressive from high compression to lossless, pyramidal, and supports regions-of-interest and multiple image types. This paper describes the CREW system and format, shows how the correct data can be quickly extracted from a CREW file to support a variety of target devices, describes the mechanisms needed for panning, zooming, and fixed-size compression, and explains the superior performance on bi-level and graphic images.

Very high speed entropy coding

Efforts to build high-speed hardware for many different entropy coders are limited by fundamental feedback loops. A method that allows for parallel compression in hardware is described. This parallelism results in extremely high rates, 100 million symbols/second or higher. The system is generalizable to any lossless or lossy system with deterministic decompression. Prototype hardware that divides the data into multiple streams that feed parallel coders is presented. The problem of efficient transmission of multiple streams of variable-length coded data is solved by a unique coded data interleave method.<<ETX>>

A new wavelet-based approach to sharpening and smoothing of images in Besov spaces with applications to deblurring

The problem of image enhancement arises in many applications such as scanners, copiers and digital cameras. Enhancement often includes a denoising and a deblurring or sharpening step. Similar to image compression, state-of-the-art denoising techniques use wavelet bases instead of Fourier bases since wavelet domain processing provides local adaptation in smooth and non-smooth parts due to the theoretical link between wavelets and smoothness spaces. In this paper the same smoothness spaces are used to propose a way of performing sharpening and smoothing of signals with wavelets (WSS) in Besov spaces. As an application the completely wavelet-based enhancement of a scanned document is discussed.

JPEG 2000-like access using the JPM compound document file format

Compound document images are usually high resolution and high quality images that include color, graphics, and images in addition to text. The need for good compression is important for storage and transmission. Due to the large size, even compressed, it is often difficult to access document images quickly and efficiently for display on monitors. The nascent JPM file format enables the best compound document image compression in terms of rate-distortion. Although JPM allows the use of JPEG 2000, access into a JPM file is limited by the access features of the older coders used. JPEG 2000 is an image coding system that allows access to lower resolutions, progressive bit-rates, and regions of interest. This paper describes methods for using JPEG 2000 in conjunction with older binary coders in a JPM file. Using these techniques it is possible to get close to the best rate-distortion performance and have access into the file.

Compression with reversible embedded wavelets with an enhanced binary mode

Compression with reversible embedded wavelets (CREW) is a unified lossless and lossy continuous-tone still image compression system. Wavelet coefficients are encoded in a bit-significance embedded order, allowing lossy compression by truncating the compressed data after encoding. CREWs context-based coding, called Horizon coding, takes advantage of the spatial and spectral information available in the wavelet domain and adapts well to the lessor significant bits. CREWs capabilities have been enhanced to include a binary mode for compression of binary and graphic images. This also improves compression on some images that do not use the full dynamic range. The binary mode encodes bit-planes of the image without using the transform. This JBIG-like system uses the resources already available in the CREW system. This paper introduces some basic concepts of CREW and describes the binary mode in detail.

Pixel and semantic capabilities from an image-object based document representation

This paper reports on novel and traditional pixel and semantic operations using a recently standardized document representation called JPM. The JPM representation uses compressed pixel arrays for all visible elements on a page. Separate data containers called boxes provide the layout and additional semantic information. JPM and related image-based document representation standards were designed to obtain the most rate efficient document compression. The authors, however, use this representation directly for operations other than compression typically performed either on pixel arrays or semantic forms. This paper describes the image representation used in the JPM standard and presents techniques to (1) perform traditional raster-based document analysis on the compressed data, (2) transmit semantically meaningful portions of compressed data between devices, (3) create multiple views from one compressed data stream, and (4) edit high resolution document images with only low resolution proxy images.

Device selective quantization for reversible wavelets

Compression with reversible embedded wavelets (CREW) consists of three major parts: a wavelet transform, an embedded context model, and a binary entropy coder. The wavelet transform is a special implementation of high quality wavelet which provides perfect reconstruction with finite precision coefficients. The context model describes the wavelet coefficients in a particular order with conditional probability estimates. Finally the FSM-coder, a binary entropy coder with functionality similar to the QM-coder, is used to generate the final code stream.

Physics and image data compression

We show how several basic image compression methods (predictive coding, transform coding, and pyramid coding) are based on self-similarity, and a 1/f2 power law. Phase transitions often show self-similarity which is characterized by a spectral power law. Natural images often show a self-similarity which is also characterized by a power law spectrum which is near 1/f2. Exploring physical analogs leads to greater unity among current methods of compression and perhaps lead to improved techniques.