Abstract: A method of and system for generating reliability information for a noisy signal received through a noise-introducing channel. In one embodiment, symbol-transition probabilities are determined for the noise-introducing channel. Occurrences of metasymbols in the noisy signal are counted, each metasymbol providing a context for a symbol of the metasymbol. For each metasymbol occurring in the noisy signal, reliability information for each possible value of the symbol of the metasymbol is determined, the reliability information representing a probability that the value in the original signal corresponding to the symbol of the metasymbol assumed each of the possible values. In another embodiment, error correction coding may be performed by adding redundant data to an original signal prior to transmission by the noise-introducing channel and performing error correction decoding after transmission.

Abstract: A method for encoding and decoding a sequence is provided. The method comprises searching a set of candidate trees varying in size for a tree T having a plurality of states. Tree T provides a structure that relatively minimizes code length of the sequence from among all the candidate trees. The method further comprises encoding data conditioned on the tree T, which may be a generalized context tree (GCT), using a sequential probability assignment conditioned on the states of the tree T. This encoding may use finite state machine (FSM) closure of the tree. Also provided are methods for decoding an encoded binary string when the encoded string includes a full tree or generalized context tree, as well as decoding an encoded string using incomplete FSM closure, incremental FSM, and suffix tree construction concepts.

Abstract: Use of Generalized Context Trees, a means for assigning a unique state from a finite set to any string, is provided. The method optionally refines the generalized context tree into a refined generalized context tree having a finite state machine (FSM) property. Refining occurs whenever the generalized context tree does not have the finite state machine property. Alternately, a method for constructing a representation of a source usable within an FSM is provided, comprising evaluating a node comprising a suffix tail and verifying the suffix tail is included in the representation, and inserting at least one node to the representation when the suffix tail is not in the representation.

Abstract: A method and apparatus for processing a received digital signal that has been corrupted by a channel is disclosed. The method includes storing the received digital signal and receiving a partially corrected sequence of symbols that includes an output of a preliminary denoising system operating on the received digital signal. Information specifying a signal degradation function that measures the signal degradation that occurs if a symbol having the value I is replaced by a symbol having the value J is utilized to generate a processed digital signal by replacing each symbol having a value I in a context of that symbol in the received digital signal with a symbol having a value J if replacement reduces a measure of overall signal degradation in the processed digital signal relative to the received digital signal as measured by the degradation function and the partially corrected sequence of symbols.

Abstract: An apparatus and method for processing a received signal that has been corrupted by a channel to generate a processed signal having less signal corruption than the received signal is disclosed. The apparatus stores the received signal, information specifying the probability that a symbol having a value I will be converted to a symbol having a value J by the channel, and information specifying a signal degradation function that measures the signal degradation that occurs if a symbol having the value I is replaced by symbol having a value J. The controller replaces each symbol having a value I in a context of that symbol in the received signal with a symbol having a value J that minimizes the overall signal degradation in the processed signal relative to the underlying noise-free signal as estimated via the observed statistics within that context.

Abstract: A number of methods and systems for efficiently storing defective-memory-location tables. A asymmetrical-distortion-model vector quantization method and a run-length quantization method for compressing a defective-memory-location bit map that identifies defective memory locations within a memory are provided. In addition, because various different compression/decompression methods may be suitable for different types of defect distributions within a memory, a method is provided to select the most appropriate compression/decompression method from among a number of compression/decompression methods as most appropriate for a particular defect probability distribution. Finally, bit-map compression and the figure-of-merit metric for selecting an appropriate compression technique may enable global optimization of error-correcting codes and defective memory-location identification.

Abstract: An image is compressed by selectively performing at least one of palettization and interframe coding on certain regions of the image. The regions are adaptively determined.

Abstract: Compression and reconstruction of a digital image are both performed by accessing a plurality of color caches corresponding to different chromatic contexts, selecting a color cache for a pixel value being processed, and using information in the selected color cache to predict a value for the pixel being processed.

Abstract: An image is compressed by selectively performing at least one of palettization and interframe coding on certain regions of the image. The regions are adaptively determined.

Abstract: A method of decoding an embedded bitstream includes the steps of reading encoded subsequences in the bitstream as ordered, decoding at least some of the ordered subsequences, and combining the subsequences to obtain reconstructed data. The encoded subsequences are read in order of decreasing expected distortion reduction per expected bit of description.

Abstract: The method of prefetching data into cache to minimize CPU stall time uses a rough predictor to make rough predictions about what cache lines will be needed next by the CPU. The address difference generator uses the rough prediction and the actual cache miss address to determine the address difference. The prefetch engine builds a data structure to represent address differences and weights them according to the accumulated stall time produced by the cache misses given that the corresponding address is not prefetched.

Abstract: A method of generating an embedded bitstream from quantized Wavelet transform coefficients includes the steps of separating the quantized coefficient bit-planes into a plurality of subsequences, ordering the subsequences according to decreasing expected distortion reduction per expected bit of description, encoding the subsequences, and appending the encoded subsequences to the bitstream as ordered. The subsequences may be ordered according to a priori assumptions about the expected distortion reduction per expected bit of description. The subsequences may be coded by adaptive run length coding such as adaptive elementary Golomb coding.

Abstract: An image compression system having a causal, context-based, single-pass adaptive filter encoder that encodes pixel values using multiple context-based threshold values. In the general case, the threshold value is a function of the context of a pixel being encoded. In one specific embodiment one threshold value is used in non-run mode contexts and another threshold value is used in run mode contexts. A single threshold decompressor may decode images encoded using the multi-threshold encoder of the invention. Other systems and methods are disclosed.

Abstract: A lossless image compression encoder/decoder system having a context determination circuit and a code table generator. The image compressor uses the context of a pixel to be encoded to predict the value of the pixel and determines a prediction error. The image compressor contains a context quantizer that quantizes the context of pixels. The image compressor counts the error values for each quantized context and uses these counts to generate context-specific coding tables for each quantized context. As it encodes a particular pixel, the encoder looks up the prediction error in the context-specific coding table for the context of the pixel and encodes that value. To decompress an image, the decompressor determines and quantizes the context of each pixel being decoded. The decompressor uses the same pixels as the compressor to determine the context. The decompressor retrieves from the context-specific coding table the error value corresponding to the coded pixel.

Abstract: A lossless image compression encoder/decoder system having a context determination circuit and a code generator. The image compressor uses the context of a pixel to be encoded to predict the value of the pixel and determines a prediction error and maps the prediction error to a mapped value having a distribution suitable for Golomb encoding. The image compressor contains a context quantizer that quantizes the context of pixels. The image compressor determines a Golomb parameter based on the context and historical information gathered during the coding of an image. To avoid systematic prediction biases in an image, the image compressor adjusts the distribution of prediction residuals to a distribution suitable for Golomb coding. As it encodes a particular pixel, the encoder uses the Golomb parameter to determine a Golomb code for the prediction error and encodes that value. To decompress an image, the decompressor determines and quantizes the context of each pixel being decoded.

Abstract: A lossless image compression encoder/decoder system having a context determination circuit and a code table generator. The image compressor uses the context of a pixel to be encoded to predict the value of the pixel and determines a prediction error. The image compressor contains a context quantizer that quantizes the context of pixels. The image compressor counts the error values for each quantized context and uses these counts to generate context-specific coding tables for each quantized context. As it encodes a particular pixel, the encoder looks up the prediction error in the context-specific coding table for the context of the pixel and encodes that value. To decompress an image, the decompressor determines and quantizes the context of each pixel being decoded. The decompressor uses the same pixels as the compressor to determine the context. The decompressor retrieves from the context-specific coding table the error value corresponding to the coded pixel.