Wavelet Based Image Coding Schemes : A Recent Survey <s> The CREW (Compression with Reversible Embedded Wavelet) Coding <s> Compression with Reversible Embedded Wavelets (CREW) is a unified lossless and lossy continuous tone still image compression system. It is wavelet based using a "reversible" approximation of one of the best wavelet filters. Reversible wavelets are linear filters with non linear rounding which implement exact reconstruction systems with minimal precision integer arithmetic. Wavelet coefficients are encoded in a bit significance embedded order, allowing lossy compression by simply truncating the compressed data. For coding of coefficients, CREW uses a method similar to J. Shapiro's (1993) zero tree, and a completely novel method called Horizon. Horizon coding is a context based coding that takes advantage of the spatial and spectral information available in the wavelet domain. CREW provides state of the art lossless compression of medical images (greater than 8 bits deep), and lossy and lossless compression of 8 bit deep images with a single system. CREW has reasonable software and hardware implementations. <s> BIB001 </s> Wavelet Based Image Coding Schemes : A Recent Survey <s> The CREW (Compression with Reversible Embedded Wavelet) Coding <s> 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. <s> BIB002
A new form of wavelet transform based still image compression technique developed at the RICOH California Research Centre in Menlo Park, California, is the CREW BIB001 . It is both lossy and lossless compression scheme, bi-level and continuous-tone, progressive by resolution and pixel depth. The CREW can preserve the source image at encoder and quantize for the target device at decoder or transmission. It is hierarchical and progressive by nature. Three new technologies combine to make CREW possible: the reversible wavelet transform (nonlinear filters that have exact reconstruction implemented in minimal integer arithmetic), the embedded code stream (a method of implying quantization in the code stream) and a high-speed, high-compression binary entropy coder The main features of CREW are: • The same CREW code stream can be used for both lossless and lossy compression applications due to embedded quantization BIB002 . • The wavelet transform produces hierarchically ordered data and a natural means for interpolation. • The bit-significance coding of CREW allows for bitplane progressive transmission. • CREW compression is idempotent and CREW encoding and decoding can be efficiently implemented in a simple way either in hardware or software. All these features combine to make a flexible "device-independent" compression system. CREW was the motivation for the new JPEG 2000 standard. The peculiar features make CREW BIB002 an ideal choice for applications that require high quality and flexibility for multiple input and output environments, such as, continuous-tone facsimile documents, medical imagery, fixed-rate and fixed-size applications (ATM), pre-press images, image archival, World Wide Web image or graphic type, satellite images etc. Not many of these applications have ever used compression schemes since the quality could not be assured, the compression rate was not high enough, or the data rate was not controllable.