Digital Video Signal Modification TRIZ Cases

Reduced-bit-length inputs for linear regression prevent overflow in affine motion derivation, supporting practical hardware coding and consistent decoding.

Triangle-shaped prediction units partition complex video regions, while merge-list motion vectors support efficient motion compensation and image quality.

Motion-vector differences and IBC coding guide boundary strength selection, limiting unnecessary deblocking while preserving video quality.

A presence flag activates subpicture count, dimensions, positions, and loop-filter settings to improve coding efficiency and error resilience.

Predefined MVR offsets refine motion vectors in geometric partitions while selective signaling limits overhead and improves video coding efficiency.

Cost-based and mode-aware reordering puts likely merge candidates first, then truncates the list to improve video coding efficiency.

Fixed-length coding of geometric split indices simplifies video inter prediction while balancing compression performance and computational complexity.

Adaptive resolution signaling coordinates coded video layers and subpictures, reducing separate resampling for efficient decoding and display.

A predefined CTU region derives conventional intra modes from unconventional candidates to guide transform selection and MPM list construction.

Triangular block partitions combine inter- and intra-prediction to improve reconstruction quality while preserving compression efficiency.

Transform identifiers are derived from quantized coefficients and transform-specific probability distributions, avoiding separate signaling and supporting independent decoding.

Bitstream mode flags select merge, MMVD, CIIP, or partitioning options to reconstruct image blocks efficiently from prediction and residual samples.

Replacement indices and adjusted coding parameters enable subarea-specific video reduction without transcoding while preserving codec conformance.

This case selects single- or bi-direction intra prediction by angle and delta angle to improve coding efficiency around sharp edges.

Predefined intra prediction mode lists help decode multi-hypothesis blocks with lower complexity while preserving prediction accuracy and picture quality.

Excluding redundant non-VCL NAL unit counts from decoder records reduces media-file data while preserving video reconstruction and transmission.

Resetting the palette predictor at each coding-region start supports independent block decoding and reduces bit usage for less likely directions.

Separate context-state buffers by temporal sublayer improve arithmetic entropy coding synchronization between encoders and decoders.

Predefined interpolation filter sets are selected by block size and prediction mode to improve coding efficiency without excessive processing complexity.

Hierarchical first- and second-level tiles let one picture carry different resolutions, reducing bandwidth and storage demands for streaming.

Bilateral matching conditions sort chained motion vector candidates into merge lists, reducing video-coding processing and power needs.

A single indicator splits large video blocks into equal-sized subblocks, reducing partition signaling overhead and improving coding efficiency.

Unified end-of-tile and CTB-row signaling reduces duplicate byte alignment bits while preserving WPP decoding efficiency.

Separate probability models encode CCLM and regular chrominance mode bits, reducing dependency and complexity in video coding.

Categorized constraint flags let video decoders test bitstream conformance without multiple profiles, reducing interoperability complexity and user error.

Limiting chroma transform block size by color component improves video encoding and decoding efficiency for high-resolution image transmission and storage.

This coding approach selects prediction-weighted tables through bitstream flags, reducing redundant signaling while preserving high-quality video compression.

ISOBMFF tracks map spatial regions to V-PCC tiles, enabling selective decoding of point cloud areas without processing the full sequence.

Selective secondary inverse transforms use intra prediction mode and block size to improve coding efficiency while limiting processing complexity.

Affine models and sub-block motion information refine inter-prediction while structured candidate lists help control construction complexity.

Selective NAL syntax extraction assigns importance values without decoding, helping RAN transceivers schedule immersive video traffic by codec semantics.

Correlation between a current block and adjacent encoded blocks narrows intra-mode search, reducing coding time and computation.

Signalled quantization parameters let V-DMC reconstruct displacement vectors without relying on the atlas metadata sub-bitstream.

Linear scaling and averaging replace square-root and exponential normalization, reducing NN-ILF complexity and power use across block sizes.

At the decoder, reconstructed luma prediction blocks derive chroma bi-prediction weights, simplifying weight setting while supporting coding efficiency and video quality.

Cross-layer reference pictures can trigger coding errors, so DMVR is disabled selectively while same-layer motion refinement remains available.

Boundary-distance rules assign different luma and chroma filter lengths to improve picture quality and simplify deblocking hardware.

Feature information guides reconstruction-value adjustments to reduce quantization errors, color blocks, and subjective loss in flat image regions.

Slice-based GDR relabels clean picture areas as random-access points while excluding other slices to reduce decoder workload during video recovery.

Thresholded angle and distance parameters simplify geometric partitioning, reducing computation while improving video coding efficiency.

Evaluating inter-frame modes first lets the encoder skip unnecessary intra-frame calculations, improving coding speed with minimal compression loss.

This case reconstructs full-scale video blocks from scaled references using partition and intra-prediction data to improve coding efficiency.

Dynamic codec selection allocates a remaining bit budget across pixels, balancing image quality and storage use while reducing overflow risk.

The case uses hierarchical luma and chroma splitting to determine coding units, improving throughput while limiting encoding and decoding complexity.

A machine learning model selects RDOQ, SQ, or HDQ from block features, balancing video image quality against encoding computation.

Variable bin counts can stall video pipelines; buffered bin sequences decouple CABAC arithmetic decoding for real-time operation.

SbTMVP derives motion information from collocated reference blocks, improving subblock prediction accuracy and reducing video coding overhead.

Downsampled chroma displacement fields are reconstructed and upsampled with added vectors to balance mesh compression and decoding quality.

Video encoders split coding units along selectable diagonals and reuse uni-prediction motion-vector candidates to improve accuracy and coding efficiency.

Deriving contexts from neighboring blocks and motion-vector parameters limits context choices while reducing motion-vector bit requirements.