Image Enhancement TRIZ Cases

This case encodes geometry and color data for efficient 3D transmission, then analyzes user input to adapt displayed content.

A camera and orientation data establish a shared reference frame, reducing mapping effort and marker dependence during device alignment.

Multiple images with varying illumination are compared by pixel intensity change to select the least motion-affected corrected image.

Depth-data tracking uses unscented Kalman filters and adaptive model likelihoods to estimate target position during motion and rest.

Camera images and an autoencoder identify filaments leaving the guide, improving yarn path abnormality detection.

Automated shelf imaging checks product placement and empty spaces for consistent compliance.

This case adapts animal shape analysis across imaging directions to estimate weight without requiring the animal to stand on a scale.

A crawler-based radiography system distinguishes pipe insulation from the wall to map corrosion and erosion across multiple locations.

This case uses gradient thresholds, Laplace and discrete cosine transforms to remove glass ghosting from a single image.

A high-pass comparison and frequency-domain loss help CNN denoising preserve fine detail while improving SNR and SSIM.

Coregistered base and informer images generate clearer labels for machine learning detection and classification of biological structures.

This case uses patient-table keypoint detection to register optical and medical imaging coordinates without large calibration phantoms.

Visual detection, database control, and separable tool units support flexible, real-time weed treatment across varied carriers.

This case maps camera and RADAR/LIDAR object trajectories into a shared latent space to resolve coordinate and timing mismatches.

Independent image features are pooled symmetrically to expand HDR range while avoiding motion-related frame alignment.

Multi-spectral, multi-exposure imaging and verification networks pre-screen serum or plasma integrity, reducing errors and specimen waste.

This image-processing approach expands inner cell regions to separate crowded cells and measure each cell in multiplex-stained specimens.

This case fuses image and non-image features through product correlations, supporting accurate prediction of future or past states.

Automatic clustering and intensity checks locate calibration standards in unstructured lidar clouds for field-ready sensor alignment.

This case adapts webcam vital sign parameters to cohort statistics, reducing noise and tracking individual physiological changes.

Uncertainty-guided sampling supports clear medical rendering while avoiding preprocessing latency.

X-ray Talbot images provide accurate fiber orientation data for structural analysis without destructive sampling of large composites.

This case combines total-station prism tracking with multi-view images to map heavy equipment work in 3D during operation.

Motion vectors and image blending improve vehicle camera image reproduction without synchronizing to LED light sources.

Pixel-based quality metrics discard unreliable images, improving surface condition estimates for real-time agricultural operations.

Object detection and segmentation blur non-work-related areas in a see-through AR display, preserving task focus.

Imaging-specific extraction coefficients speed pigment concentration estimates.

Detecting signal polarity enables fast WASAB1 fitting of B0 and B1, producing accurate maps for MRI field correction.

Machine learning detects bad telematics installations from fastener orientation.

A trained teacher network guides monocular depth learning, helping vehicles recover scene scale without LiDAR at deployment.

Detect deformation abnormalities during medical image registration for more accurate alignment.

Depth sensors and pose-aware alignment combine partial scans into a full-body 3D model with accurate body measurements.

This evaluation system weights false estimation types by impact for more relevant tracking algorithm performance assessment.

To address VR-to-AR incompatibility, computational modules extract depth information and reformat content into multifocal virtual images.

This case separates vessel segmentation from CNN classification to limit information loss in intracranial occlusion imaging.

Two-pass skin filtering preserves realistic facial texture during stretching and compression.

Multiple detection criteria and selective user correction use reference images to improve infrastructure defect inspection accuracy.

Orthogonal polarization reduces surface glare while infrared light improves depth visibility for non-invasive lymph node and vessel imaging.

Automatic thumbnails track standard anatomical planes and reduce scanning workload.

A conversion model turns pixel distances into physical track measurements, enabling alerts for rail gaps and surface defects.

This case trains an inpainting neural network to separate same-label object instances while reducing manual guidance.

Preview blur levels before capture for intuitive background shading.

Track gaming activity despite obstructions with calibrated multi-camera vision.

This case uses machine learning to segment clothing and apply facial-expression-driven AR effects without depth sensors.

Adjusting scan timing across frames and synthesizing distance images improves resolution and range while preserving S/N ratio.

Generate diverse annotated virtual humans to train robust keypoint models.

Correct wide-angle thermal distortion to locate people accurately indoors.

A second PET volume during radiotracer bolus transit bridges functional PET data and CT angiography for accurate registration.

This case uses adaptive persistence and infinite impulse response filtering to reduce flash artifacts in low-velocity power Doppler imaging.

A camera-guided light unit activates device groups for relevant image regions, improving depth extraction while limiting power use.

Mobile data acquisition units extract motion parameters from video frames to minimize storage requirements and reduce manual review labor.

Eye and joint tracking define spatial zones in a 3D environment, resolving the trade-off between high interaction precision and increased system complexity.

Generating synthetic computed tomography images from reference data to train neural networks for precise anatomical feature preservation.

Selective illumination and high-resolution digital microscopy capture silicone oil distribution on syringe surfaces.

Stereo imaging provides depth data that corrects segmentation errors caused by visual similarity between foreground objects and complex backgrounds.

Electronic device calculates depth maps for sub-images to stitch multiple planes, eliminating internal parallax from camera misalignment.

Machine vision algorithms identify items removed from shelves, eliminating checkout lines and reducing transaction time.

A composite image processing device applies region data to differentiate pixel value selection between moving subjects and static backgrounds.

Dynamic region calibration handles non-standardized formats while maintaining precise boundary identification for fraud prediction.

A lane determination method matches camera-collected road features with high-precision map data to identify the vehicle's target lane.

Aligning point clouds from separate scans merges incomplete dental impressions into accurate models, reducing retake frequency.

An image-to-image network learns spatial features from CT scans to classify COPD without manual annotation.

A facial recognition enrollment system detects subject identity switches during image capture to maintain profile integrity.

An automated solver computes animation model control values through an objective function, reducing manual correction time while maintaining high accuracy.

A treatment support device uses a treatment light imaging unit to set a region of interest based on the irradiation position.

Depth sensors approximate digit center-lines to identify hand surfaces, resolving interference from wearable items that obscure arm features.

Coordinate conversion aligns pixel cells to axes, eliminating sensor installation errors in crash tests.

A method extracts informative features from input and infrared guide images to enhance visual quality without direct depth sensors.

An image control system selects images of interest by calculating complexity and quality scores to optimize storage usage.

A medical information processing apparatus aligns blood flow index graph orientations with conventional display standards.

Filter processing removes anomaly values from disparity images before merging, resolving horizontal streak noise that degrades object detection accuracy.

Discrete scale ratios resolve perspective magnification in ADAS optical flow without SIFT complexity.

A method estimates motion blur direction by applying artificial blur across multiple test angles to identify the orientation causing minimal image change.

Interlaced pixel lines with alternating exposure times resolve the trade-off between dynamic range and resolution in conventional Bayer sensors.

A lane pricing system uses vehicle-mounted camera and GPS data to identify travel lanes for toll calculation.

A medical image processing device extracts blood vessel regions and evaluates shape characteristics to identify abnormal portions.

A trained neural network segments MR images into bone, air, and soft tissue to generate a subject-specific magnetic susceptibility map.

A map generation device transforms image coordinates into a common system using multiple markers to create spatial data.

A medical apparatus automates reference image selection from fluoroscopic data using respiratory phase tracking.

Simplifying noisy 2D map data with traveling information resolves inaccuracy issues, producing clear 3D indoor spatial models.

A target tracking method uses deep recurrent networks to determine final positions from initial predictions based on reference image features.

A hybrid mask filter combines Gaussian and Sigmoid functions to isolate peak frequencies in spectrum images.

A calculation unit extracts image feature quantities to generate display icons for visual association with additional information.

A neural network encoder and dual decoders disentangle unique features from common image data to generate segmentation masks.

Dynamic pixel block sizing resolves the contradiction between distortion correction and moving object detection in heat haze scenarios.

A steerable endoscope system updates patient anatomy models using live camera and position signals for precise navigation guidance.

A human parsing device generates height and width distribution maps to acquire attention maps for improved feature extraction.

Dual shared buffers separate image capture from depth estimation, reducing processor burden while maintaining real-time update speeds in virtual reality scenes.

Multi-scale classifier fusion generates probability maps from pixel-level predictions to resolve subjective border detection variability in dermoscopy images.

A multicore computing system segments neural rendering into MLP feature extraction and CNN refinement stages to produce high-fidelity images.

A region determining device calculates pixel wetness likelihood to automatically select optimal monitoring areas.

Parallel processing threads compute distance derivatives to refine pose estimates, resolving latency and accuracy trade-offs in lidar mapping.

An execution module identifies and replaces sensitive data in document images to create safe training sets.

A crop yield estimation method segments fields into regions using image processing to identify representative data collection points for accurate predictions.

Automated side branch detection eliminates manual adjustment errors and enables live co-registration of angiographic and intravascular imaging modalities.

Reinforcement learning agent generates adversarial samples by incrementally adding and removing image distortions based on model sensitivity.

An information processing apparatus automatically acquires and stores display conditions based on image variation indices.

A navigation image method converts subtraction images into distinct color spaces to enhance visibility of medical instruments.

Segmenting the model allows dynamic classification updates without retraining, resolving training time constraints.

Optical horizon detection resolves IMU acceleration errors to improve maritime navigation precision.

A medical information processing system divides grouped lesion data into separate units for independent chronological tracking.

Segmenting trajectories through multiple anchor frames reduces error accumulation and improves robustness against occlusions.

Multi-aperture microscope array captures high-resolution images across a large field of view.

Segmenting camera images into valid and masking areas reduces computing power while maintaining tracking reliability for augmented reality displays.

Segments optoacoustic views and applies fluence normalization to resolve chromophore concentration measurement precision limits across larger anatomies.

Generates compact metrics from vehicle camera images to verify data integrity during processing.

Determining regularization parameters via noise equivalent counts and spatial sensitivity suppresses image noise while preserving diagnostic detail.

Log color space projection stabilizes material identification under varying illumination by separating reflectance from shadows.

Determines alignment data via patch shifts to stabilize video, reducing computation costs and latency for high frame rate processing.

A graph neural network processes segmented cell images to predict therapy effectiveness.

Area-based analysis identifies vessel orientation to correct velocity measurements and reduce color bleed artifacts in medical diagnostic ultrasound.

System stores candidate vascular bifurcation routes and selects the best match based on real-time guidewire shape similarity, reducing contrast media use.

An image processing apparatus extracts characteristic points from input images to perform signal processing and interpolation.

Processor selects preliminary reference points at straight line intersections in overlapping image frames to establish calibration geometry.

An image processing apparatus obtains a map of protrusions and recesses from captured images to determine defect presence at inspection boundaries.

Segmenting imaging functions into separate cameras prevents software attacks while maintaining accurate user positioning.

Processor detects swallowing instruction, inflow, and reflex triggering timings to resolve diagnostic accuracy versus speed trade-offs.

Augmented reality components adjust virtual object focus to match surrounding frame data.

A 3D radiation imaging system aligns symmetrical breast regions using feature positions.

Block segmentation extracts initial features from image fragments, enabling accurate detection of various tampering types across different formats.

Deep neural networks detect and correct insulator orientation in images, resolving accuracy issues in manual overhead line inspections.

Multiscale deep learning aligns noisy contours, reducing computational cost while maintaining alignment flexibility.

Automated hyperspectral fundus imaging identifies blood vessels through spectral reflection analysis and principal component extraction.

A range-finding system corrects pre-correction parallax using pixel position-specific image deviations from two imaging devices.

A dynamically reconfigurable heterogeneous systolic array generates image processing primitives from video frames to enable real-time scene analysis.

Markov random field transforms volumetric lung data into a log likelihood field for ground glass nodule identification.

Sampled data rows input to a learned neural network determine abnormality features without region extraction, reducing arithmetic processing load.

A projector uses a switchable diffuser and diffraction optical element to generate structured light patterns.

A VR headset system uses eye tracking and digital displays to simulate the cover/uncover test for precise recording of eye positions.

Server builds 3D point clouds from imagery and fits them to survey data, cutting time needed for manual measurements.

Machine learning system classifies semiconductor defects using Bayesian analysis of metrology and manufacturing data to reduce manual inspection time.

Random feature perturbation defends against adversarial attacks while preserving prediction accuracy across diverse domains.

Simultaneous correction of optical distortion and motion compensated integration re-registration reduces random noise in infrared imaging systems.

A 3D shape measurement device projects phase pattern images using stabilized light sources to capture accurate target object geometry.

Head-mounted display downloads shared maps to resolve indoor positioning accuracy without GPS or hardware beacons.

Normality models capture illumination statistics to reduce false positives during background subtraction under dynamic lighting conditions.

A multifactor pixel-level analysis detects purple fringe artifacts within an image processing pipeline to enable dynamic correction adjustments.

A state determination apparatus calculates feature values from deflection and surface displacement measurements to assess structural integrity.

An image processing method detects high dynamic range sources and applies specific color adjustment values to ensure accurate display output.

A predictive SLAM system compares real-time frames with stored landmark data to determine headset position.

Scaling test images to match training parameters resolves the trade-off between identification accuracy and database size.

Software calculates camera rotation using sensor-derived translations and epipolar unit vectors for early Structure-from-Motion integration.

An adaptive video subsampling system uses objectness segmentation to create binary masks that reduce computational load while preserving critical visual data.

Deconvolution reverses low-pass filter blur before segmentation, correcting calcium blooming artifacts and restoring lumen boundary precision.