Digital Video Signal Modification TRIZ Cases

A generative compression network quantizes feature map variance to produce variable bit rate outputs using a single trained model.

Deriving illumination compensation from neighboring signal statistics eliminates explicit signaling overhead while maintaining cross-view prediction accuracy.

A transform-based image coding method selects multiple transforms using an index derived from block tree and partition types.

Spatially selective encoding partitions panoramic video into tiles to reduce energy consumption on resource-limited devices.

SEI messages indicate extraction modes to ensure sub-bitstream decoding compliance while optimizing size.

Leverages base layer intra modes as probable candidates to improve compression efficiency while reducing computational complexity.

A video decoder applies multiple Sample Adaptive Offsets to reconstructed blocks for enhanced image quality.

A motion vector angular prediction process stores candidates in a list to perform inter prediction on video coding units.

Derives weighting-value predicting information for current view texture blocks using neighboring view data to enhance coding efficiency.

Encoder selects block sizes using a decision tree comparing predefined combinations to reduce encoding time.

A video encoder compares blocks to previous frames to identify background content for adaptive encoding.

Adaptive block partitioning and codebook coding resolve memory usage trade-offs by dynamically adjusting bit depth based on saturated maximum values.

A quantization controller adjusts scales using diagonal frequencies and motion data to optimize video encoding.

Iterative anchor pixel prediction updates the reference region with selected pixels, resolving complex discontinuities in image blocks.

A multi-view video coding method calculates an optimal warping offset to correct disparity information for precise view prediction.

Segmenting intra prediction modes into MPM and non-MPM sets improves accuracy while reducing bitstream size through conditional variable length coding.

Applying intra block copy at the slice level resolves coarse picture-level control trade-offs, enabling finer prediction accuracy for text and graphics.

Dynamic candidate marking enables parallel inter prediction processing in video coding blocks.

Ordered reference lists resolve arbitrary view ID assignment bottlenecks by structuring viewpoint positions for efficient multi-viewpoint image coding.

Encoding video with droppable frames allows decoders to skip non-reference images during playback.

Segmenting media data into tiles distributes processing loads across multiple decoders, enabling real-time 8K image playback.

Segmenting video regions retains entropy coding states across frames, reducing re-initialization overhead and improving compression efficiency.

Layered video encoding resolves the conflict between full resolution 3D delivery and legacy set-top box compatibility.

A video encoder determines motion vector resolution per area to perform inter prediction encoding.

Re-partitioning reference macroblocks to match current partition geometry for precise motion vector prediction.

Implicit scalability dimension identifiers in HEVC parameter sets reduce coding complexity while maintaining high image quality.

An embedded codec circuitry allocates refinement bits based on visual quality measures to improve image fidelity.

A tensor-product B-spline predictor generates metadata to reconstruct mapped images from source color grades.

Bitstream indicators enable embedded coefficient sign embedding, resolving prediction accuracy versus complexity trade-offs in video codecs.

Dividing images into zones applies intra block copy prediction selectively, reducing computational complexity and memory storage requirements.

Dynamic tool selection via block size flags reduces bitrate losses and improves codec adaptability for diverse use cases.

A rate controller adjusts video compression parameters based on real-time coding block load.

An image decoding apparatus decodes division information to perform binary tree division on coding nodes.

A video signal processing device corrects motion vectors using picture order count differences to reconstruct current blocks.

Pre-analysis uses down-scaled images to determine affine parameters, reducing computational complexity while maintaining prediction accuracy.

A bitrate-adaptive segmentation system determines chunk boundaries using inter-prediction and intra-prediction bit costs from a first pass encoding log.

A motion estimation apparatus uses user input to determine displacement coordinates for video block matching.

A hash-based block matching method identifies candidate blocks using compact values to accelerate video encoding.

A decoding apparatus derives an HMVP candidate list and updates an AMVP list to generate prediction samples.

Fixed-size pixel blocks allow independent random access and parallel decompression, reducing memory bandwidth and power consumption.

An adaptive bitrate controller adjusts media streams based on real-time network conditions.

A video encoding method restricts chroma block splitting based on size thresholds to reduce bitstream overhead.

Dynamic interpolation filter selection adapts reference sample buffers to prediction modes, reducing memory requirements while maintaining video quality.

Visual data processing adds a timestamp difference indication to RTP packets, enabling correct decoding of bi-directional predicted frames.

Segmenting neural network syntax into distinct information units resolves interoperability complexity while maintaining compression efficiency.

A video processing method determines a cost metric for target motion candidates based on matching costs to optimize encoding operations.

Encoding apparatus calculates costs for sub-blocks to select optimal hierarchy, reducing processing time.

Separate 3D and texture streams allow metadata-driven key frame selection to reduce data volume while preserving image quality.