Digital Video Signal Modification TRIZ Cases

Block-size-based secondary inverse transform control cuts parsing delay and buffering while preserving image quality in image decoding.

Specific NAL units signal target output layers and temporal IDs, reducing bitstream parsing while improving multilayer image coding efficiency.

Merged-view reshaping and metadata improve stereoscopic HDR video compression while preserving 3D quality across HDR and SDR displays.

Long-term motion vector candidates are added to the HMVP list to improve motion compensation, compression, and decoding efficiency.

Grouping similar photos into shared compression containers cuts redundant image data and reduces cloud storage requirements.

Multiple bitstreams at different encoding scales keep lower-data video arriving under network fluctuations, reducing freezes in conferencing and online classes.

Switching between context and bypass coding for block coefficients cuts CABAC overhead while preserving precision in high-bitrate video.

By transforming only a predefined block region, this case cuts video decoding complexity, memory access, and processing power demand.

Decoded pictures are stored by spatial resolution in the buffer, enabling smoother bitrate-driven resolution changes without upscaling delays.

Weighted reference blocks derived from template matching improve inter prediction accuracy while cutting residual bits and signaling overhead.

PDPC-based color block prediction skips unnecessary refinement to lower intra coding complexity while preserving video coding performance.

Filtering adjacent reference pixels into a subset improves cross-component colour prediction while cutting model complexity and memory bandwidth.

Matrix-weighted intra prediction improves block mode selection in video coding, raising quality and coding efficiency without excessive complexity.

Color-specific intra prediction candidates and filtered reference pixels improve prediction accuracy and coding efficiency in image encoding.

Bitstream encoding of 3D generative models cuts point-cloud storage and bandwidth while preserving arbitrary-view image output.

A learning model predicts rate-distortion clusters from video complexity to set bitrate targets with lower compute cost and more uniform quality.

Conditional Rice parameter signaling for transform skip residuals cuts unnecessary bits while preserving video quality in coefficient coding.

Critical-frame adaptive loop filtering cuts VVC encoding passes and latency by reusing filter coefficients while preserving video quality.

Unequal CU weights can make BDOF costly, so this case bypasses optical flow per coding unit to cut complexity and resource use.

Neighbor-based geometry transform inference cuts RR-IBC signaling overhead while preserving intra-prediction efficiency in video coding.

Sub-block transforms limit transform target regions and code last significant coefficients to cut video transform time and data load.

L-shaped video block partitions better match object boundaries, improving rate-distortion performance without excessive coding complexity.

Reference sample padding and selective filtering support wide angular intra prediction in non-square blocks with lower decoding complexity.

By deriving tile count from slice header conditions and picture header structure, video decoding cuts signaling overhead without harming reconstruction.

Switching 8-tap and 6-tap interpolation filters by block size improves video coding quality while reducing processing load and memory bandwidth.

Weighted combining of two reference blocks improves image prediction accuracy while reducing inter-prediction data and bitstream bitrate.

A constrained intra prediction mode search improves image compression and reconstruction quality while avoiding the cost of full mode testing.

Grouped and downsampled neighboring samples feed linear or affine transforms to improve intra prediction while lowering video coding complexity.

Block-size-based switching between 8-tap and 6-tap interpolation filters improves affine video coding quality while reducing bandwidth and load.

Bitstream-carried usage flags let video quantization adapt to human viewing or AI tasks, improving coding efficiency and reconstruction.

Prioritizing top-over-left spatial candidates cuts motion index overhead and improves triangle prediction coding performance.

Adaptive filter patterns match local gradients in reconstructed blocks, improving diagonal edge handling and video coding efficiency.

Separate external and internal OBMC reduce blocking artifacts and improve coding efficiency in high-resolution video coding.

Filtering decoded residuals with a weighted mask reduces low-resolution blocking artifacts while preserving coding efficiency and picture quality.

Segmenting an AVS3 bitstream into RTP packets with payload headers enables real-time video transport while preserving stream feature information.

Residual prediction from reference blocks cuts bits for intra modes and residual signals while preserving image decoding accuracy.

Fixed-length clip index coding and shared luma-chroma parameters cut loop filter complexity and speed up video encoding and decoding.

Selective bi-directional optical flow corrects block prediction only within an existing reference region, cutting memory bandwidth and processing load.

Restricted top and left boundary samples correct inter prediction luma and chroma shifts while reducing memory use and pipeline latency.

Conditional affine and sub-block TMVP syntax improves motion prediction accuracy while limiting bitstream overhead and decoding load.

Warped video frames keep bitrate low while separately encoding eyes and mouths to avoid uncanny face distortions.

Reordered motion candidate lists and selective pairwise averaging improve video coding efficiency without excessive list construction overhead.

Disabling lossy coding tools and switching residual handling enables exact video reconstruction while preserving high-frequency detail.

Depth difference maps replace transmitted motion vectors and full depth maps, cutting 3D video bitrate while preserving rendering quality.

Adaptive chroma QP offset decoding by CU size and tree type improves image compression efficiency while reducing buffer needs.

Preconfigured partition candidates and adaptive coding order improve subblock intra-prediction accuracy while limiting image coding complexity.

Geometric block partitioning and weighted prediction averaging improve video compression for oblique or curved edges with less boundary data.

A shared neural network mode filters both chroma components in video coding, cutting complexity and processing time without hurting rate-distortion performance.

Corrected motion vectors, boundary padding, and selective filtering improve video decoding efficiency without excessive complexity.

Dynamic sublayer selection lets image bitstreams match quality needs while reducing transmission and storage overhead.