Image Enhancement TRIZ Cases

Color-based line sampling reduces operation data while avoiding background brightness interference for accurate orientation detection.

MR headset detects real-world objects and modifies virtual element appearance to resolve user safety risks from occlusion.

A polarization imaging device captures simultaneous multi-directional light to separate pixel signals and calculate surface normal lines.

Image processing apparatus calculates intensity histograms to highlight lesion pixels in medical scans.

AAR algorithms quantify body composition via virtual landmarks, eliminating manual segmentation bottlenecks.

A face deblurring method aligns images to a mask and matches grid patterns against reference dictionaries.

Clustering untagged item pixels with neural networks identifies representative reference images, eliminating the need for external defect-free references.

Oblique camera positioning eliminates precise distance requirements for measuring boiling water reactor fuel channel deflection from a single image.

Longitudinal shear waves generated by coaxial coverslip excitation resolve axial elasticity gradient detection limits in semi-infinite media.

Automated inspection apparatus analyzes component exterior data to determine mounting states without manual input.

CCD imaging captures grain reflection intensity to calculate silicon wafer crystal orientation.

A modification unit aligns position and time data from separate image captures to generate a unified virtual viewpoint image.

A recognizing unit selects a smaller number of dimensions among feature vectors to match local areas in images.

A depth conflict reduction system dynamically modifies user interface element positions to avoid visual clashes in stereoscopic video.

Overlaying surgical limbus images onto diagnostic views with adjustable transparency resolves side-by-side alignment errors.

Computer-based method measures collision or gap values between teeth using specific directional vectors derived from 3D digital models.

A gaming system detects fiducial markers to transform geometric data for augmented reality overlays.

A two-stage encoder-decoder network automates wire segmentation in high-resolution images.

Generative adversarial networks superimpose traffic light images onto real roadway scenes to create augmented training data for deep neural networks.

A travelling road estimating apparatus adjusts a Kalman filter response level based on edge point stability to maintain accurate lane tracking.

A control apparatus identifies unrecognizable areas around a moving object and transmits targeted warning information to external devices.

A supporting CNN transforms virtual driving scenes into realistic images, resolving domain shift and reducing training costs.

A neural network module classifies blood vessels as veins or arteries in ultrasound images to guide medical procedures.

Segmenting convolutional neural network layers by object importance reduces computational overhead during image analysis.

A workstation generates joint-visualization images by assigning visualization priority to pixels across multiple functional imaging datasets.

A system generates ortho-image mosaics using prioritized stacking and bundle adjustment to align source pixels accurately.

An automated system extracts intensity and shape features from image data to classify biological cells.

A fisheye camera system projects object contours onto virtual planes to determine distance without external sensors.

A noise reduction section uses motion vectors calculated from bright normal light images to clean special light images in endoscopy.

Aligning 2D dynamic object data with 3D structural models resolves the trade-off between high-fidelity mapping and operational cost.

A defect inspection device uses infrared imaging to correct ultrasonic coordinate deviations for precise wafer analysis.

A determining unit calculates projection thickness parameters based on region of interest data to generate clear projection images.

Automated image processing detects pre-analytical errors in biological samples, resolving operator reliability issues without adding manual complexity.

A lake water volume monitoring method fuses shoreline, area, and altimetry data to derive accurate change sequences.

Correlating initial and subsequent captures through confidence metrics resolves accuracy-complexity trade-offs in augmented reality point cloud generation.

A monocular camera system determines object location by projecting known reference points into a two-dimensional image to form a polygon.

Computer system identifies anatomical features in medical images to determine registration parameters for accurate alignment.

A stacked autoencoder reconstructs dynamic PET concentration images from mixed tracer data using deep learning.

Atrous convolutional neural networks extract feature maps from stereo images to generate disparity maps.

A pre-trained machine-learning model predicts time-related information to build a further model for semantic context in medical imaging.

Segmenting instrument regions in 2D projections enables 3D reconstruction that provides real-time guidance without adding physical tracking complexity.

Measuring the actual point spread function via image processing replaces simplified models, resolving distance calculation errors in monocular cameras.

Clustering pixels determines hole bottom contours in semiconductor specimens, resolving accuracy issues from wide shape variations.

A voxel-based analytical approach registers and normalizes medical images to create parametric response maps.

Automated digital imaging replaces manual measurement with 3D reconstruction, resolving inter-clinician variability in compression garment fitting.

A dictionary generation unit creates customized detection data from training inputs and network structure restrictions.

A multi-object tracking system leverages spatial relationships between objects to identify targets using user-defined templates.

A variational principle method calculates river surface flow velocity using image acquisition and energy functional optimization.

Generative adversarial networks predict internal anatomy from surface data to create synthetic X-ray images for machine learning training.

A fundus observation apparatus specifies tomographic scan locations using analyzer-derived lesion candidates from fluorescent imaging data.