Image Enhancement TRIZ Cases

Overlay depthmap data on panoramic images to identify selected objects, resolving foreground background confusion in navigation displays.

An adaptive defogging controller adjusts parameters based on detected fog density to produce clear images.

Multi-energy projection datasets enable metal artifact reduction in computed tomography imaging systems.

A controller detects defects by comparing weighted pixel values from substrate images.

A processing system assigns depth values to video foregrounds and estimates surface normals to augment images with virtual lighting effects.

An AI system distinguishes squamous cell carcinoma lesions from non-cancerous ones in epidermolysis bullosa patients using deep learning image analysis.

Automatic closed-loop ultrasound plane steering uses prediction networks to localize medical devices and anatomical structures, reducing view finding time.

A predictive system segments building surfaces to monitor coating integrity using computer vision algorithms.

A 3D sensor system projects multiple linear patterns simultaneously to capture synchronized images for rapid point-cloud generation.

Automated feature selection replaces manual interpretation to improve measurement precision and productivity in brain imaging analysis.

MRI and DTI analysis correlates implant pose with therapeutic outcomes to resolve placement precision versus procedure time trade-offs.

Parsing a k-distance data tree reduces nearest neighbor search complexity from O(N^2) to O(log n) for semiconductor device measurements.

Raw ultrasound image processing via trained model avoids resolution mismatch errors while reducing computational load.

Depth sensor data streams enable touchless interaction on a wearable device, avoiding social interruption caused by manual input.

Sensors detect obscured obstacles and project depth cues onto pillars to resolve visual obstruction.

Partitioning MRI sequence instructions into non-equally spaced kernels reduces FPGA processing complexity while maintaining microsecond timing precision.

A method calculates absolute depth from image coordinates and predefined height to determine real-world positions.

A visual feedback loop projects patterned images onto a display to refine part profiles, resolving measurement accuracy limits in complex geometries.

Rectifies degraded video frames by mapping pixel data from a reference image to polygonal facial regions, restoring clarity under low bandwidth conditions.

Dividing decoded feature maps into grid cells allows unique weighted convolution filters to optimize segmentation accuracy for repetitive road patterns.

A dual neural network architecture processes input tensors through separate feature detection and filtering paths to reduce computational load.

Ordinal classification model determines confidence through binary classifier consistency checks on cumulative auxiliary classes.

A clustering algorithm segments CT image super-pixels to extract calcified spot contours and calculate vascular indexes.

A radiographic imaging apparatus determines image capturing conditions based on electrical signals from pixels to enable proper exposure.

An online training model learns global patterns to classify and track targets in video streams.

Convolutional neural networks generate volumetric heatmaps to determine 3D human poses from single images.

A mobile terminal control unit extracts face objects and modifies image regions using distance-based correction coefficients to restore subject shape.

Modeling velocity changes between scanlines using inertial acceleration improves pose estimation accuracy without significant computational overhead.

Masking background regions in detection images allows a trained neural network to differentiate sealed and unsealed wafer box clips despite positioning errors.

A neural network architecture constructs density maps to predict object counts and locations using image-level supervision.

Alert discriminator compares foreground intensity to background levels, filtering false alarms from falling snow while preserving relevant stationary objects.

A processor calculates image enhancement coefficients from channel data to weight beam-formed signals for improved ultrasound imaging.

Generates analogue brain wave data from eye video sequences to predict fatigue states, avoiding cumbersome real brain wave detection equipment.

A data processing device outputs coordinate system setting information to specify axis and attribute correspondence for image generation.

Knowledge graph information matrices encode domain-specific driving scene attributes for base model training.

Alternating-sign readout gradients suppress metal-induced artifacts in multi-spectral MRI, recovering resolution without extending scan time.

Texture mapping real images onto 3D models generates diverse training data, reducing inference time for complex objects.