Digital Video Signal Modification TRIZ Cases

A method converts volumetric data to point cloud partitions projected onto two-dimensional images for encoding.

An image decoder generates prediction signals by extracting pixel information from already-decoded areas at integer multiples of a vector distance.

A decoder extracts metadata from video streams to support image processing modules.

Grouping transform coefficients by template magnitude reduces context model quantity while maintaining entropy coding precision.

Partitioning video coding blocks allows blending candidates from regular Merge lists, reducing computational complexity and memory bandwidth.

Constraining the depth lookup table value range replaces Exp-Golomb codes, reducing bitstream size while maintaining mapping accuracy.

Tree-based block partitioning derives local prediction modes to reduce data volume while maintaining high-resolution image quality.

Estimates specific regions to set high quality encoding parameters, reducing delay while maintaining accuracy.

A video encoding method selects candidate intra-frame prediction modes using optimal modes from downsampled and adjacent units.

Exponential partitioning replaces straight lines with curved boundaries to reduce motion compensation prediction errors and improve compression efficiency.

Segmented subblock processing computes refined linear model parameters to resolve pipelined decoding delays and maintain measurement precision.

A video coding method selects distinct transform kernel sets based on whether adjacent or non-adjacent reference lines drive intra prediction.

Packed frame encoding resolves the contradiction between consistent 3D effect reliability and adaptability to varying viewing conditions.

A panoramic video coding method assigns quantization parameters to multiple layers of spherical circumferences.

A video encoder creates virtual temporal affine candidates using neighboring sub-blocks to enhance motion compensation diversity.

A video codec selects optimal macroblock modes using hexagonal and diamond search patterns for motion vector estimation.

A scalable video encoding standard segments virtual reality content into base and enhancement layers for selective client-side decoding.

A subblock-based temporal motion vector prediction method calculates corresponding positions using center sample data to improve coding efficiency.

A computational resource management system adjusts encoding parameters based on audience measurement and video content complexity.

A fast block coder with optimized truncation processes significance and magnitude information using adaptive coding techniques.

Truncated unary coding reduces code amount for offset values, maintaining high-frequency components and preventing video blurriness.

A parallel video decoder processes half frames to reduce decoding time.

A video compression apparatus acquires and compresses frames from multiple imaging regions operating at distinct frame rates.

Segmenting palette structures into independent luma and chroma components resolves split tree structure mismatches in video encoding.

An image encoding apparatus selects prediction or run length encoding based on pixel position.

Variable block division modes align sub-block boundaries with image texture, resolving the trade-off between structural complexity and fitting precision.

Segmenting video streams into sub-ranges with distinct bit-rates reduces file size while maintaining target perceptual quality across variable content.

Segmenting motion candidates by type and prediction mode improves coding efficiency while managing complexity.

An image encoding apparatus performs variable-length encoding on pixel blocks to generate compressed data streams.

Computes weighting coefficients from temporal brightness variations to enhance motion prediction accuracy in scalable video encoding.

A parallel image encoding method processes upper-right blocks before lower-left ones to accelerate intra prediction.

Decrementing picture order count values in the decoded picture buffer before resetting resolves cross-layer misalignment and improper output order.

Converting raw data to full color via demosaicing enables arbitrary magnification ratios while preventing moire artifacts and pseudo color degradation.

A dynamic bit allocation mechanism optimizes image compression by adjusting data distribution based on operation information.

Updates codewords via iterative training to resolve initialization sensitivity and improve encoding accuracy.

Segmenting intra block copy buffers into local and non-local sets enables non-local sample usage, resolving coding efficiency limits in conventional designs.

Adaptive weighting of enhancement and base layer pixels resolves the trade-off between prediction accuracy and compression efficiency in scalable video coding.

A neural network jointly despeckles and compresses single-look complex SAR images using self-supervised training on real and imaginary parts.

A cross-component sample adaptive offset method selects luma samples via vertical coordinate indexing to classify chroma data.

Advanced motion estimation encodes video frames using direct external memory access and variable block sizes, reducing bandwidth usage and memory requirements.

Depth-based motion searching restricts calculation regions to reduce encoding complexity while maintaining image quality and improving efficiency.

Nonlinear warps deform pixel shapes based on saliency to preserve face proportions during video scaling.

A video coding apparatus determines a target frame structure based on B-frame thresholds to match current scenarios.

A Cross-Component Sample Adaptive Offset method classifies chroma samples using luma values to enhance coding efficiency.

A system on chip adjusts video bit rates using spatial filters and quantization parameters to manage data flow.

Shared quantization parameters decode grouped feature maps, reducing computational burden and transmission overhead while maintaining precision.

Dynamic coefficient generation eliminates lookup tables, reducing memory demands while maintaining prediction accuracy across subpixel positions.