Digital Video Signal Modification TRIZ Cases

Adapting weight matrix transition widths via template matching for video decoding blocks.

A video coding method segments target objects and backgrounds into separate feature maps for efficient neural network processing.

A transmit end switches between HEVC and AVC coding manners based on real-time state information.

A neural network media coder uses optimized probability distribution parameters for entropy coding to preserve compression efficiency.

A warped motion compensation model projects pixels to non rectangular patches using neighbor block parameters.

Cloud device renders field of view images in advance using predicted user posture and location changes, reducing display latency for cloud VR systems.

Interleaves enhancement data within standard DVD video streams to enable stereoscopic playback on existing optical disc players.

Temporal scaling adjusts motion vectors by reference frame distance, resolving the trade-off between prediction precision and computational complexity.

Filters NAL units against output layer sets to extract sub-bitstreams, resolving bandwidth complexity trade-offs in video coding.

A hardware video encoding pipeline generates primary and secondary encodes using distinct prediction modes for parallel processing.

Template matching predicts chroma components from decoded samples, resolving the trade-off between prediction accuracy and computational complexity.

A video encoder evaluates signaling costs to filter tool settings before full evaluation.

A coding device selects luma and chroma quantization parameter relationship tables based on slice type, prediction mode, and luminance value.

Segmenting fast and read-only memory for adaptive and non-adaptive context models reduces power consumption while maintaining compression efficiency.

Decoder extracts independent reference sub-regions to reduce bandwidth usage and computational costs during video coding.

Dynamic filtering tab selection minimizes residual signal intensity in video encoding while controlling calculation complexity.

A unified inverse transform processing unit dynamically configures arithmetic logic to handle multiple video coding standards through segmented control stages.

A video optimization server dynamically adjusts compression settings using real-time radio frequency data from baseband units.

A video processing method refines motion vectors through a two-step inter-prediction process to enhance compression performance.

A NAL unit header syntax structure signals Gradual Decoding Refresh and Dependent Random Access Point picture types in video coding streams.

An image processing apparatus sets a region of interest and adjusts encoding quality based on detected moving objects.

A video encoding method selects inter prediction modes and constructs candidate lists to generate prediction blocks.

A generative adversarial network analyzes scene objects to generate optimized capture plans for dynamic media compression.

Forcing small prediction units in bi-predicted slices to use uni-prediction reduces memory bandwidth consumption during video coding.

A video coding system uses temporal prediction reference chains to generate multiple frames from single source frames.

A video decoding apparatus generates new motion vector predictors by averaging existing spatial and temporal candidates within a unified candidate list.

A video encoding method uses transformation index information to determine adaptive transformation unit structures for efficient data processing.

Selective position-dependent weighting reduces processing complexity while maintaining high prediction accuracy in video blocks.

Encoding device selects candidate filter parameter sets for video blocks to minimize rate-distortion cost.

Encoding video into switchable inter-coded and decoder reset representations manages decoding complexity during viewport changes in 360-degree streaming.

Deriving disparity vectors from depth block subsets reduces computational complexity while maintaining peak signal-to-noise ratio for 3D video coding.

A decoded picture buffer management method invokes additional bumping after each picture removal to free space and prevent overflow.

Deriving illumination compensation flags from prediction candidates during frame rate up-conversion reduces encoding complexity.

Preserves artistic intent during compression by applying local fidelity adjustments to specific content regions.

An array server combines video streams into a multi-source stream, allowing clients to switch angles instantly without delaying the main streaming server.

A single binary tree encodes coding unit prediction and prediction unit partition mode, reducing transmission overhead while maintaining encoding precision.

Constructing a composite track box merges multiple elementary tracks to reduce processing complexity while maintaining delivery adaptability.

Applying multi-hypothesis prediction via a non-regular merge list refines motion information and prediction samples to improve coding efficiency.

A de-blocking filter adjusts boundary strength based on prediction modes to preserve high-frequency details in video data.

Extracting coding information like motion vectors enables frame-rate up-conversion on compressed or uncompressed video, overcoming bandwidth limitations.

A video encoder adjusts group of pictures frame counts by determining time intervals between adjacent frames.

Derives filter parameters on the decoder side using reconstructed frames to suppress noise without transmitting data.

A neural network analyzes decoded video frame edges to detect macroblocking artifacts without reference data.

Adaptive filtering of reconstructed luma samples based on chroma format improves cross-component linear model prediction accuracy.

Tile-based picture partitioning with selective size information encoding improves decoding accuracy while reducing bitstream length overhead.

Deriving internal sub-block motion vectors from refined edge data improves prediction accuracy in video encoding.

Consolidating separate lookup tables into a single structure reduces computational overhead and memory usage during encoding.

A video coder segments syntax elements using significance flags and greater-than-N flags to determine coding contexts from shared tables.