Abstract: Wavelet based multiresolution video representations generated by multi-scale motion compensated temporal filtering (MCTF) and spatial wavelet transform are disclosed. Since temporal filtering and spatial filtering are separated in generating such representations, there are many different ways to intertwine single-level MCTF and single-level spatial filtering, resulting in many different video representation schemes with spatially scalable motion vectors for the support of different combination of spatial scalability and temporal scalability. The problem of design of such a video representation scheme to full the spatial/temporal scalability requirements is studied. Signaling of the scheme to the decoder is also investigated. Since MCTF is performed subband by subband, motion vectors are available for reconstructing video sequences of any possible reduced spatial resolution, restricted by the dyadic decomposition pattern and the maximal spatial decomposition level.

Abstract: A method for representing an omni directional-like image by capturing an omnidirectional-like image and determining a representation format that is commonly applicable to any image acquisition system that is able to capture the omnidirectional-like image. The captured omnidirectional-like image is mapped onto the determined representation format.

Abstract: A method for representing an omnidirectional-like image by capturing an omnidirectional-like image and determining a representation format that is commonly applicable to any image acquisition system that is able to capture the omnidirectional-like image. The captured omnidirectional-like image is mapped onto the determined representation format.

Abstract: Methods and apparatuses for performing arithmetic encoding and/or decoding are disclosed. In one embodiment, an arithmetic decoder comprises a sequencer to generate a context identifier for an event of an event sequence, a probability estimator to determine a value for a LPS and a probability estimate for the LPS, and a decoding engine that includes a range register to assign a value to a range for the LPS. The value is based on the probability estimate, a value stored in the range register and the context identifier to a range for the LPS if the context identifier is not equal to an index and the value is not based on the value stored in range register if the context identifier is equal to the index. The decoding engine further determines a value of a binary event based on the value of the range for the LPS and bits from an information sequence.

Abstract: Methods and apparatuses for performing arithmetic encoding and/or decoding are disclosed. In one embodiment, the method for creating a state machine for probability estimation comprises assigning probabilities to states of a look up table (LUT), including setting a probability for each state i of the states equal to the highest probability of the LPS multiplied by the adaptation rate to the power i, where i is a number for a given state and the adaptation rate is smaller than 1. The method also comprises generating state transitions for states in the LUT to be transitioned to upon observing an MPS and an LPS, wherein the next state to which the state machine transitions from a current state when an MPS is observed is a next state higher than the current state if the current state is not the highest state and is the current state if the current state is the highest state.

Abstract: Methods and apparatuses for performing arithmetic encoding and/or decoding are disclosed. In one embodiment, the method for creating a state machine for probability estimation comprises assigning probabilities to states of a look up table (LUT), including setting a probability for each state i of the states equal to the highest probability of the LPS multiplied by the adaptation rate to the power i, where i is a number for a given state and the adaptation rate is smaller than 1. The method also comprises generating state transitions for states in the LUT to be transitioned to upon observing an MPS and an LPS, wherein the next state to which the state machine transitions from a current state when an MPS is observed is a next state higher than the current state if the current state is not the highest state and is the current state if the current state is the highest state.

Abstract: Methods and apparatuses for performing arithmetic encoding and/or decoding are disclosed. In one embodiment, a method for encoding data comprises coding a plurality of events in an event sequence to produce encoded data and generating a bitstream using the encoded data, including adding zero or more stuffing bits to the bitstream after the encoded data. The zero or more stuffing bits operate to substantially maintain a relationship between an amount of events encoded, a number of blocks being coded, and a number of bits in the bitstream.

Abstract: Video compression algorithms typically represent visual information by a combination of motion and texture data. Motion data describes the temporal relationship between the content of a frame and that of a previous frame. This invention describes a method and apparatus for efficiently encoding motion data, particularly in the presence of horizontal and/or vertical motion boundaries.

Abstract: Arithmetic encoding and/or decoding are performed using an arithmetic encoder and/or decoder, respectively. The arithmetic decoder may include a sequencer to generate a context identifier for an event of an event sequence, a probability estimator to determine a value for a LPS and a probability estimate for the LPS, and a decoding engine that includes a range register to assign a value to a range for the LPS. The value is based on the probability estimate, a value stored in the range register and the context identifier to a range for the LPS if the context identifier is not equal to an index and the value is not based on the value stored in range register if the context identifier is equal to the index. The decoding engine further determines a value of a binary event based on the value of the range for the LPS and bits from an information sequence.

Abstract: An arithmetic encoder is provided for converting an event sequence comprised of a plurality of events to an information sequence comprised of at least one information piece, and includes a core engine for receiving an event of the event sequence, and a probability estimate from a probability estimator, and generating zero or more pieces of the information sequence responsive to the received event and the probability estimate by bounding the ratio of events to information pieces. An arithmetic encoder is provided that is capable of constraining a number of events in at least one event sequence as a function of the number of generated information pieces in at least one information sequence.

Abstract: The present invention relates to an image processing apparatus, and to realize improved lossless compression of images more efficiently. A first predictor 11 generates a prediction signal P out of peripheral pixel values supplied from a pixel sequence generator 2. A second predictor 12 generates a prediction signal Q out of the peripheral pixel values supplied from the pixel sequence generator 2. An adder 4 subtracts the prediction signal P from the current pixel value to thereby calculate a prediction error signal M. When the prediction signal Q is greater than the prediction signal P, an inverter 14 inverts the polarity of the prediction error signal M to consequently generate a prediction error signal N. And an entropy encoder 5 allocates a code word in accordance with the prediction error signal N generated by the inverter 14.

Abstract: A method and apparatus is disclosed herein for decoding data (e.g., video data) using transforms. In one embodiment, the decoding process comprises scaling a block of coefficients using a scaling factor determined for each coefficient by computing an index for said each coefficient and indexing a look-up table (LUT) using the index. The index is based on a quantization parameter, a size of the block of coefficients, and a position of said each coefficient within the block. The method also comprises applying a transform to the block of scaled coefficients.

Abstract: Wavelet based multiresolution video representations generated by multi-scale motion compensated temporal filtering (MCTF) and spatial wavelet transform are disclosed. Since temporal filtering and spatial filtering are separated in generating such representations, there are many different ways to intertwine single-level MCTF and single-level spatial filtering, resulting in many different video representation schemes with spatially scalable motion vectors for the support of different combination of spatial scalability and temporal scalability. The problem of design of such a video representation scheme to full the spatial/temporal scalability requirements is studied. Signaling of the scheme to the decoder is also investigated. Since MCTF is performed subband by subband, motion vectors are available for reconstructing video sequences of any possible reduced spatial resolution, restricted by the dyadic decomposition pattern and the maximal spatial decomposition level.

Abstract: A method of representing light field data by capturing a set of images of at least one object in a passive manner at a virtual surface where a center of projection of an acquisition device that captures the set of images lies and generating a representation of the captured set of images using a statistical analysis transformation based on a parameterization that involves the virtual surface.

Abstract: A method for representing an omni directional-like image by capturing an omni-directional-like image and determining a representation format that is commonly applicable to any image acquisition system that is able to capture the omni-directional-like image. The captured omni-directional-like image is mapped onto the determined representation format.

Abstract: Methods and apparatuses for performing arithmetic encoding and/or decoding are disclosed. In one embodiment, an arithmetic decoder comprises a sequencer to generate a context identifier for an event of an event sequence, a probability estimator to determine a value for a LPS and a probability estimate for the LPS, and a decoding engine that includes a range register to assign a value to a range for the LPS. The value is based on the probability estimate, a value stored in the range register and the context identifier to a range for the LPS if the context identifier is not equal to an index and the value is not based on the value stored in range register if the context identifier is equal to the index. The decoding engine further determines a value of a binary event based on the value of the range for the LPS and bits from an information sequence.

Abstract: Methods and apparatuses for performing arithmetic encoding and/or decoding are disclosed. In one embodiment, the method for creating a state machine for probability estimation comprises assigning probabilities to states of a look up table (LUT), including setting a probability for each state i of the states equal to the highest probability of the LPS multiplied by the adaptation rate to the power i, where i is a number for a given state and the adaptation rate is smaller than 1. The method also comprises generating state transitions for states in the LUT to be transitioned to upon observing an MPS and an LPS, wherein the next state to which the state machine transitions from a current state when an MPS is observed is a next state higher than the current state if the current state is not the highest state and is the current state if the current state is the highest state.

Abstract: The present invention relates to an image processing apparatus, and to realize improved lossless compression of images more efficiently. A first predictor 11 generates a prediction signal P out of peripheral pixel values supplied from a pixel sequence generator 2. A second predictor 12 generates a prediction signal Q out of the peripheral pixel values supplied from the pixel sequence generator 2. An adder 4 subtracts the prediction signal P from the current pixel value to thereby calculate a prediction error signal M. When the prediction signal Q is greater than the prediction signal P, an inverter 14 inverts the polarity of the prediction error signal M to consequently generate a prediction error signal N. And an entropy encoder 5 allocates a code word in accordance with the prediction error signal N generated by the inverter 14.