Abstract: Embodiments of the present invention comprise methods and systems for signaling tone map data to an image recipient.

Abstract: Embodiments of the present invention comprise methods and systems for high dynamic range video coding.

Abstract: Embodiments of the present invention relate to methods and systems for communicating pixel prediction modes between video encoders and decoders.

Abstract: Embodiments of the present invention comprise systems and methods for quantization or dequantization of data related to video wherein reduced bit depth intermediate calculations are enabled.

Abstract: Embodiments of the present systems and methods for quantization or dequantization of data related to video wherein reduced bit depth intermediate calculations are enabled.

Abstract: Methods and apparatus for video contrast enhancement are disclosed. A pixel level threshold is set for an input video frame in a video sequence. For pixel levels in the input video frame that are below the threshold, an adaptive contrast-enhancing function is applied. For other pixel levels, a scene-stable mapping function is applied. This contrast enhancement method can improve the contrast in darker areas of a scene depicted in the video sequence, without destroying the intended light levels for a scene or causing temporal brightness fluctuations in the enhanced video sequence.

Abstract: Embodiments of the present invention relate to methods and systems for communicating pixel prediction modes between video encoders and decoders

Abstract: Embodiments of the present invention relate to methods and systems for estimating a pixel prediction mode to be used in a video encoding or decoding process.

Abstract: Embodiments of the present invention relate to methods and systems for ordering pixel intra-prediction modes.

Abstract: A method is provided for the quantization of a coefficient. The method comprises: supplying a coefficient K; supplying a quantization parameter (QP); forming a quantization value (L) from the coefficient K using a mantissa portion (Am)(QP)) and an exponential portion (xAe(QP)). Typically, the value of x is 2. In some aspects of the method, forming a quantization value (L) from the coefficient K includes L=K*A(QP)=K*Am(QP)*(2Ae(QP)). In other aspects, the method further comprises: normalizing the quantization value by 2N as follows: Ln=L/2N=K*Am(QP)/2(N-Ae(QP)). In some aspects, forming a quantization value includes forming a set of recursive quantization factors with a period P, where A(QP+P)=A(QP)/x. Forming recursive quantization factors includes forming recursive mantissa factors, where Am(QP)=Am(QP mod P), and forming recursive quantization factors includes forming recursive exponential factors, where Ae(QP)=Ae(QP mod P)−QP/P.

Abstract: Methods and apparatus for constructing a grafted codebook, encoding symbols using a grafted codebook, and decoding codewords formed using a grafted codebook are disclosed. A grafted codebook is formed by piecewise modeling an input probability distribution on a number of modeling intervals, and then selecting a set of modeling distributions that minimize the redundancy of the piecewise model on the modeling intervals. An infinite code is then selected for each interval, and offsets are calculated for the codes. The codes are then merged into a grafted codebook where each code contributes codewords on its interval. The offsets are used to ensure that the resulting codebook is valid from a cumulative probability standpoint.

Abstract: Embodiments of the present invention comprise systems and methods for quantization or dequantization of data related to video wherein reduced bit depth intermediate calculations are enabled.

Abstract: Methods and apparatus for constructing a grafted codebook, encoding symbols using a grafted codebook, and decoding codewords formed using a grafted codebook are disclosed. A grafted codebook is formed by piecewise modeling an input probability distribution on a number of modeling intervals, and then selecting a set of modeling distributions that minimize the redundancy of the piecewise model on the modeling intervals. An infinite code is then selected for each interval, and offsets are calculated for the codes. The codes are then merged into a grafted codebook where each code contributes codewords on its interval. The offsets are used to ensure that the resulting codebook is valid from a cumulative probability standpoint.