Image Enhancement TRIZ Cases

Camera system detects patient surface motion to identify regions of interest, reducing user time spent locating observation points during radiation therapy.

A capture structure with a point-symmetrical optical property profile enables precise position determination through frequency domain transformation.

Computational inversion of double-exposure shearograms recovers single-exposure images without additional spotting imagers.

A turbine inspection system identifies key frames using positional offsets between detected perimeter edges and a reference blade pose.

Automated landmark synchronization aligns prone and supine CT colonography scans to reduce interpretation time and increase polyp detection accuracy.

A camera and sensor augmented reality orientation system fuses optical and inertial data to determine device position.

A hybrid mesh-volumetric representation combines a proxy rough mesh with neural texture thin volumes to generate accurate 3D digital objects.

A surgical navigation system generates 3D bone models and provides overlay visual information to guide accurate fracture reduction.

Dynamic backlight compensation adjusts drive signal start and end times based on front porch periods to resolve motion blur in variable frequency displays.

An FMCW radar system employs an RF switch to multiplex polarization channels, resolving the trade-off between device complexity and image resolution.

A controller uses forward-looking cameras to generate mine profiles ahead of the shearer.

A rasterizing and thinning image processing device adjusts pixel resolution to standard levels.

Iterative tracking determines object-specific representations from region proposals, reducing computational complexity while maintaining recognition accuracy.

A processing apparatus synthesizes images across varying spatial frequencies to support stable feature point extraction.

A sample applicator determines its position relative to a substrate using reflected image detection for precise fluid dispensing.

A computer-based system automatically registers 3D CT landmarks with real-time 2D laparoscopic images using derived coordinate sets.

Spectral transforms process row and column mean values to filter noise from captured image frames.

Analyzing topological relationships between road boundaries to automatically identify intersections in electronic maps.

A data analysis system corrects retinal nerve fiber layer thickness using optic disc macular inclination angles and blood vessel intersections.

Segment cardiovascular images into patches to refine blood vessel contours and improve lesion detection accuracy.

A dual neural network apparatus generates parametric re-grading weights to map high dynamic range image lumas into secondary display ranges.

Sequential spatial and temporal filtering in YCbCr space removes noise while preserving motion object clarity.

Switching between coarse and precise interpolation modes reduces energy consumption by 38% while maintaining scene reconstruction accuracy.

IP2CP formulation merges pre and post disaster images to reduce manual labeling time while maintaining classification accuracy.

Motion-based hybrid chroma subsampling applies variable resolution across image regions to reduce data size while preserving fidelity in low-motion areas.

Extract planar features from 3D LiDAR data to determine motion, overcoming unstable point features in occluded scenes.

Rotating an eccentric camera around the instrument axes generates stereoscopic views that resolve coordinate accuracy without external baselines.

A remote weapon control device extracts targets from images and determines a shooting sequence to enable rapid engagement.

Augmented reality devices capture time-synchronized video, audio, and spatial data to create comprehensive procedural documentation.

Processor selects target blocks with varying sample periods to generate depth information from reference and target images.

Grouping pixel values into clusters consolidates denoising and sharpening, reducing latency while avoiding edge artifacts.

Computer vision extracts cranio-facial vectors from digital images to automate personality-based smile design, eliminating time-consuming manual questionnaires.

Discrete wavelet transform fuses holographic and lens-based images to resolve the trade-off between wide field-of-view and color accuracy.

Spatially varied noise filtering adjusts signal processing based on anatomical feature extent in surgical microscope imaging data.

A 3D reenactment system generates immersive vehicle representations for accident reconstruction.

Local quality and dynamics principles adjust thresholds based on neighborhood statistics to resolve classification accuracy versus speed trade-offs.

A dynamic image analysis apparatus extracts feature amounts from frame images to calculate temporal changes.

Automated CT image segmentation identifies intracranial space attributes to guide twist drill craniostomy placement.

Automated cameras detect traffic violations using object identification models, replacing manual police monitoring to improve enforcement coverage.

A guidewire artifact suppression method filters scan line data and applies dynamic logarithmic processing to reconstruct clear ultrasound images.

An image processing apparatus adjusts collation methods based on object feature similarity to improve person retrieval accuracy.

Image processing device divides image data into partition cells to calculate a skin tone estimation value and select outliers for white point detection.

Spatiotemporal saliency maps weight features by relevance for specific actions, reducing background clutter interference and improving detection accuracy.

A thermal camera corrects image distortions using a generated correction matrix derived from a moving temperature reference.

Drone system locates avalanche victims using electronic device detection to overcome slow manual search speeds.

An image forming system generates reference data from preprinted sheets to determine relative positions of additional images.

A vehicle vicinity supervising device calculates parallax offset values using sub pixel estimation to correct stereo image data.

A head-mounted device uses gaze tracking to direct an optical sensor toward external objects for color measurement.

A display control unit superimposes a marker distribution image on a performer's face to guide precise marker placement.

A deep convolutional neural network aggregates radiological features across CT slices to detect osteoporotic vertebral fractures missed during routine review.

A surveillance headcount system matches moving objects against object models to extract foreground images for accurate pedestrian detection.

Comparing measured value sequences identifies parallax issues in sensor fusion, ensuring accurate distance estimates while minimizing computational complexity.

Portable devices obtain 3D feature locations using camera images and inertial sensor data, replacing expensive specialized scanning hardware.

A vehicle image processing apparatus compresses identical pixels into key frames and different pixels into delta frames.

Hardware processor superimposes non-contact point clouds with morphological images to estimate biological part positions within sensor coordinates.

A fixture holds an imaging device at a fixed distance from composite surfaces to determine image scaling factors using calibration objects.

Processor module generates synthetic T1-weighted and CT images from single MRI scan data using deep learning algorithms.

Node-based geometry and attribute coding encodes point cloud data via tree structures, enabling low latency transmission without waiting for full encoding.

Statistical spot selection lowers false alarm rates while maintaining detection range and reducing calculation time.

A disparity estimation system generates multiple maps with successively increasing sizes through cascaded multi-stage processing.

A 3D image annotation system outputs a representative image to select target pixels and display relevant slices.

Gradient analysis of the nose bridge region detects eyewear, reducing computational complexity and manpower costs.

Machine learning models detect fractures from high-resolution images to estimate dynamic hydraulic properties for reservoir simulation.

Automated classification of infarct, ischemic, and normal tissue classes resolves the contradiction between diagnostic accuracy and image generation speed.

Image analysis detects critical dimensions and periodicity in self-assembled block copolymer structures.

An automated measurement system captures hand geometry using 3D scanning and landmark detection to generate precise anthropometric data.

Normalize sinogram data before deep learning denoising to remove streaks and heavy-tailed noise from reconstructed images.

A depth prediction machine learning model generates compressed log scene measurement maps by applying a logarithmic function to normalize image ranges.

Reduced resolution neural network segments video frames using previous masks, lowering compute cost to under five GOPS and extending battery life.

A computer program adjusts endoscope LED light amounts based on learning model recognition results to optimize illumination.

Automated dopamine transporter check system processes 3D brain scans into standardized 2D images using transfer learning models.

Automated staircase renovation element production uses marker-based image analysis to extract precise dimensions for custom manufacturing.

A video processing system extracts trajectory interaction features from pedestrian and vehicle movements to detect potential illegal drug deals in real-time.

A luminance compensation apparatus adjusts color signal brightness based on saturation levels to enhance display output.

Top and bottom clamping aligns images of unequal height before matrix comparison, filtering noise from added or removed rows.

A toboggan-based approach extracts pulmonary embolism candidates directly from CT angiography voxels without vessel segmentation.

Attention mechanisms sample ranked contexts to resolve convolutional artifacts in indoor images, ensuring high-fidelity object removal.

Synchronizes probe data with the cardiac cycle to automate segmentation, reducing manual intervention time while maintaining high anatomical accuracy.

View hotspots and indicator signals guide mask block generation, resolving object recognition errors in complex or artistic shapes.

Depth maps from structured light guide deconvolution filters to sharpen images, resolving the trade-off between fixed focus limitations and diagnostic clarity.

Converting non-image data into training images enables automated anomaly detection, reducing downtime and expertise requirements.

Graph convolutional neural network integrates multimodal MRI data into structured brain graphs for disease prediction.

A computerized method segregates images into intrinsic components by identifying dominant single reflectance regions within the input data.

Triangulation-based endoscope calculates object distance and view angle to render a dynamic size mark, resolving complexity in spatial coordinate measurement.

Detecting subject orientation parameters to compute weighted visual similarity scores, resolving accuracy drops across varying orientations.

A scanning system uses processor-based point cloud registration to align reference models with scanned data for precise calibration.

Scanning semiconductor devices with laser light to acquire electrical signal characteristics for generating pattern images.

Switching to image correlation resolves insufficient scale-based accuracy for multi-field-of-view measurements.

A mobile terminal extracts image quality data from multiple displays via camera to synchronize output settings.

Derives coil-specific noise indices to adjust removal degrees, resolving inconsistent image quality across reception coils.

Iterative structured light processing recovers super-resolved images from limited raw data.

Region growing algorithm isolates aneurysm dome points to generate refined masks for volumetric image data.

A hand-raising detection device converts 3D spatial data into an overhead view image for silhouette extraction.

A method selects sensing data for machine learning models by evaluating agreement between detection results from sensors with different precision levels.

Adjustable correction elements compensate for refractive index variations and slide thickness changes, preserving high numerical aperture performance.

A signal processing device uses a neural network to extract feature quantities from sensor input signals.

A system analyzes image data using anthropometric heuristics to assess content appropriateness for specific contexts.

Iterative reconstruction and reprojection determine the real rotation axis, reducing arc-shaped artefacts in 3D reconstructions.

Automated 3D modeling identifies missing fissures to improve emphysema treatment selection accuracy.