A compression and decompression system in which a reversible wavelet filter are used to generates coefficients from input data, such as image data. The reversible wavelet filter is an efficient transform implemented with integer arithmetic that has exact reconstruction. The present invention uses the reversible wavelet filter in a lossless system (or lossy system) in which an embedded codestream is generated from the coefficients produced by the filter. An entropy coder performs entropy coding on the embedded codestream to produce the compressed data stream.

Method and apparatus for compression using reversible wavelet transforms and an embedded codestream

Disclosed herein is a method of storing and of progressively transferring a still image so that it can be conveniently previewed during the transfer and so that a user can terminate the transfer at an early stage if the image turns out to be undesirable. The methods of the invention include transforming the image into a plurality of decomposition levels using a discrete wavelet transform. Each decomposition level comprises a plurality of subimages which allow reconstruction of an image representation of the still image. The decomposition levels are transmitted beginning with a base decomposition level providing a low level of image resolution and then proceeding with decomposition levels providing increasingly higher levels of image resolution. Within each decomposition level, rows of the various subimages are arranged or interlaced together in contiguous blocks, so that all data for a single row, at a single decomposition level, is transmitted together. At the receiving end of the transfer, the row blocks are reconstructed and displayed as they are received. The invention enables the initial display of a low resolution image which is gradually updated and sharpened, on a row-by-row basis, until a desired high resolution is achieved. The user may terminate the transfer at any point.

Progressive image transmission using discrete wavelet transforms

The imaging system that is described below is an image streaming system which is different from traditional compression systems. It eliminates the necessity to store a compressed version of the original image, by streaming ROI data using the original stored image. The imaging system of the present invention also avoids the computationally intensive task of compression of the full image. Instead, once a user wishes to interact with a remote image, the imaging server performs a fast preprocessing step in near real time after which it can respond to any ROI requests also in near real time. When a ROI request arrives at the server, a sophisticated progressive image encoding algorithm is performed, but not for the full image. Instead, the encoding algorithm is performed only for the ROI. Since the size of the ROI is bounded by the size and resolution of the viewing device at the client and not by the size of the image, only a small portion of the full progressive coding computation is performed for a local area of the original image. This local property is also true for the client. The client computer performs decoding and rendering only for ROI and not the full image. This real time streaming or Pixels-On-Demand™ architecture requires different approaches even to old ideas. For example, similarly to some prior art, the present imaging system is based on wavelets. But while in other systems wavelet bases are selected according to their coding abilities, the choice of wavelet bases in the present imaging system depends more on their ability to perform well in the real time framework. The system of the present invention supports several modes of progressive transmission: by resolution, by accuracy and by spatial order.

System and method for transmitting a digital image over a communication network

Compression/decompression using reversible embedded wavelets

A method and apparatus for encoding and decoding data is described. The present invention includes a method and apparatus for generating transformed signals in response to input data. In one embodiment, the transformed signals are generated using a reversible wavelet transform. The present invention also includes a method and apparatus for compressing the transformed signals into data representing a losslessly compressed version of the input data. In one embodiment, the present invention decomposes the input data using a non-minimal length reversible filter. The decomposition may be performed using multiple one-dimension filters.

Apparatus for compression using reversible embedded wavelets

A method for decomposing signals into efficient time-frequency representations for data compression and recognition which uses adaptable wavelet basis functions and concentrates a signal or image's information to a higher degree than methods based on the discrete fourier transform, the discrete cosine transform, the standard wavelet transform and known adaptive transform techniques. The purpose of the present invention is to enable data signals and images to be stored and transmitted very efficiently. The time-frequency plane is broken up into subspaces. The method determines the optimum basis function for each of the subspace regions. Basis functions are chosen such that much of the information in the signal is contained in a small number of coefficients. The resulting coefficients form a set that represents the signal in the most concentrated manner.

Weiping Li

Papers

Method for decomposing signals into efficient time-frequency representations for data compression and recognition