Digital Video Signal Modification TRIZ Cases

Segmenting stitched multi-channel video into encoder-safe sub-images enables user-defined output resolution without exceeding encoder limits.

Weighted dual merge prediction combines two motion-compensated candidates to improve video compression efficiency with manageable complexity.

A similarity flag lets attribute tiles be derived from atlas tiles, cutting 3D data redundancy while preserving flexible tile definition.

Block prediction derives LIC indicators from multiple motion candidates to remove ambiguity and improve video coding efficiency and quality.

Multiple template types are selected by block shape, size, and mode to improve intra-frame prediction accuracy and video compression.

Adaptive block-level reference picture reordering cuts inter-prediction signaling bits while preserving video quality and limiting distortion.

Non-reference picture flags guide previous-picture selection for correct POC derivation, improving video compression efficiency and storage use.

Delta-angle switching selects single or bi-direction intra prediction for 90-180° modes, improving sharp-edge coding efficiency.

Block-based blending of deblocking and neural network filters cuts block noise while preserving edges across luma, chroma, and transfer functions.

Motion-shift estimation and template-matched candidate refinement improve inter prediction accuracy while reducing residual error and bitrate.

Wrap-around padding improves subpicture boundary reconstruction in coded video, boosting compression efficiency and subjective visual quality.

Adaptive SGPM blending and multi-mode intra prediction improve partition accuracy, cut bitrate, and manage encoding complexity.

Adaptive coding flags use content type, boundary, gradient, and neighbor modes to improve video coding quality and efficiency.

Pre-stored merge motion vector data replaces iterative candidate comparisons, cutting inter-frame coding time and complexity.

Combining spatial, temporal, and chained motion vectors improves bi-prediction accuracy and cuts residual data in complex motion scenes.

Decoder-side intra mode derivation maps neural prediction blocks to standard intra modes, improving residual coding efficiency in video decoding.

Adaptive reference-area selection improves cross-component chroma prediction from reconstructed luma, boosting video compression efficiency.

Transform-domain coefficients and non-transform context are split into two NN filter inputs to lower decoding complexity and memory bandwidth.

By coding fully padded units with adjusted bit allocation or fixed length, slice reconstruction quality stays more uniform across padded pictures.

Adaptive matrix intra prediction selects block-specific MIP modes to cut signaling and complexity while preserving image coding quality.

Bit ranges are coded separately and signaled with bit offsets, preserving significant bits when high-bit-depth video uses lower-bit-depth codecs.

Short-distance intra prediction refines residual blocks line by line to cut residual bit signaling and improve video coding efficiency.

A base decoder and enhancement layer split improves video quality while limiting decoder changes, hardware upgrades, and power use.

Pre-signaled subpicture size, position, and ID mapping improve VVC/H.266 coding efficiency, error resilience, and parallel decoding.

SEI-signaled neural post-filters use available preceding pictures to improve video fidelity while limiting bandwidth and processing overhead.

Inferring missing constituent rectangle identifiers from prior values cuts signaling overhead while preserving grouping in scalable and multiview video coding.

Partitions a picture into subpictures with different NAL unit types, improving video compression efficiency while limiting transmission and storage cost.

Aligned IRAP and GDR flags help decoders manage unavailable reference pictures and avoid crashes in multi-layer video streams.

Selecting NNPF input pictures from previous CLVS improves VVC decoding efficiency while controlling signaling and bandwidth overhead.

Tree-type and block-size based chroma QP offset signaling improves coding efficiency while lowering decoder cost and buffer requirements.

GPU-memory encoding and selective IDR/P-frame delivery cut latency and resource use in real-time synthetic video streaming.

Motion-compensated boundary padding improves VVC reconstruction near picture edges, raising video quality while limiting signaling overhead.

A unified intra-prediction circuit uses angle and noise-block decisions to support H.264, H.265, and AV1 with lower area and power.

Placing the picture header NAL unit before the first VCL unit removes PH ID bits while preserving picture association and coding efficiency.

Neighbor-block mode checks replace LUT-based intra prediction mapping, reducing memory overhead while preserving prediction accuracy.

Signal partitions are mapped into INR parameter images so standard codecs can exploit redundancy and improve coding efficiency with lower complexity.

Similarity checks between intra prediction sub-modes let coders replace redundant predictors, improving compression efficiency and reducing data size.

Restricted ALF taps and fixed-filter processing cut video coding complexity and latency while preserving reconstructed video quality.

Bitstream energy syntax lets decoders decide whether to apply neural network post-filters, balancing video quality against power use.

Selective OBMC inheritance from motion vector candidates improves video coding efficiency while limiting signaling and computational overhead.

SEI-guided neural network post-filter control adapts decoder energy use to user QoE needs, reducing waste without fixed video processing.

Comparing derived parameters across intra coding sub-modes lets coders replace similar predictors, cutting redundancy and bitstream size.

Matching pixels with flip patterns improves string prediction alignment and expands vector candidates for higher video compression.

HoG and VIPM derived before block fusion guide transform set selection, improving video compression efficiency with less decoding overhead.

Using PDPC-updated previous lines, this case improves directional intra prediction to reduce luminance discontinuities and boost compression efficiency.

Regularized autocorrelation and cross-correlation modeling improves chroma-from-luma block prediction for more efficient video compression.

Metadata-driven neural-network color filtering balances video quality and energy use by adapting post-processing to content and energy events.

Using different top and left reference line offsets improves VVC intra prediction for positive angular modes while balancing coding complexity.

SEI metadata carries NNPF energy parameters so decoders can decide when to apply neural post-filtering and limit video-processing power use.

Uses temporally adjacent and IBC reference samples in adaptive loop filtering to improve reconstructed video quality and coding efficiency.