Image Enhancement TRIZ Cases

A polarization degree correction unit minimizes noise impact on object surface information by applying gain based on calculated noise variance.

A raindrop-image-recognition model replaces detected droplets with prior scene regions to restore image clarity.

Automated image processing replaces manual sketching to eliminate safety risks and reduce construction delays.

A camera system images a visual target with an embedded GPS receiver to derive precise 3D coordinates and establish a transformation matrix.

A trained neural network adapts projection matrices from initial static models and captured X-ray data to generate 3D results.

Surgical microscopy systems record and store annotated images for machine learning training, minimizing disruption to medical workflows.

Block match denoising processes image portions in real-time using pixel averaging, reducing latency while maintaining quality.

A pseudo-three-dimensional neural network processes sagittal, transverse, and coronal planes to denoise medical image volumes.

Image processing apparatus adapts high dynamic range content using luminance conversion metadata for accurate display output.

Inertial orientation sensors fused with optical data determine camera position and orientation in a global reference frame.

A vehicle system detects driver gaze and hand position to automatically activate turn indicators based on traffic conditions.

Information processing device generates projection images matching compression member sizes for mammography apparatuses.

Position encoding feature maps integrate camera parameters into neural networks, ensuring reliable 3D visual perception across varying camera configurations.

Image processing device derives positional deviations between projection images using pseudo-projection techniques.

A lithographic pattern inspection method counts remaining features in region-of-interest images to identify defects.

A visual localization map update system calculates relative and absolute poses from consecutive images to maintain accurate spatial positioning data.

A classification model trained on pseudo-stained images automates cell analysis in histological slides, reducing pathologist workload and equipment costs.

A generative neural network creates a template image from good parts to identify defects by comparing input images against the reference.

A region extraction model learning apparatus generates composited learning data by combining person regions with background images.

An image processing apparatus updates tracking target identification information when subjects are detected in video frames.

Wireless tracker and camera calibration board normalize imaging parameters to resolve high device cost and variable focal length accuracy issues.

Multimodal deep learning system identifies predictive biomarkers from histopathology images and clinical data to guide personalized treatment decisions.

Neural networks generate an alignment index to classify image and LiDAR data points, correcting misalignment errors in autonomous vehicle sensors.

A neural network assigns quality scores to images during iterative reconstruction to automate assessment and optimization.

A method reduces correction complexity by aligning multi-directional image deformation along a single axis through intermediate rotation.

Predicting errors at block boundaries reduces longitudinal memory storage and minimizes image distortion during parallel halftone processing.

A calibration method corrects moving obstacle posture using static reference matching.

Processing elements multiply input data with weights using only non-zero values.

Camera arrangement uses a balancer and shading corrector to maintain uniform sensor signal mapping across offset fields of view.

A neural network extracts a degradation map from degraded images to perform pixel-wise feature modulation.

Modified marching cubes algorithm segments objects into discrete cubes to calculate mass contributions from volume data.

An image analysis device estimates subject color by capturing images with and without illumination to isolate external light effects.

Software estimates live deer age from photos using morphometric data, replacing invasive tooth examination methods.

Three-dimensional imaging detects buried defects in 3D NAND wafers by extracting spurious optical signals while preserving critical depth information.

A detection device segments object position and class identification into separate units with distinct class definitions.

A respiratory motion detection apparatus projects an illumination pattern onto a person to track chest deformation for signal determination.

A cyber-physical system analyzes electromagnetic spectrum image frames using convolutional and recurrent neural networks to detect asset aberrations.

Binary spherical gradient illumination separates diffuse and specular reflectance, eliminating the need for polarized light sources or restrictive viewpoints.

A processing system extracts specular intensity profiles from RGBD sequences to estimate light source position without dedicated imaging hardware.

Resample deep learning feature maps to generate activation maps, reducing manual marking workload while maintaining detection accuracy.

Generating virtual CT images from SPECT or PET data and a single CT scan reduces radiation exposure while maintaining image registration accuracy.

Color analysis detects document edges without relying on shadows, resolving accuracy issues in low-contrast scanning scenarios.

Image processing apparatus derives mammary gland percentage using fat tissue pixels from multiple compression states.

Dynamic distance range adjustment adapts to varying workpiece heights, preventing clipped whites and ensuring accurate shape reflection in grayscale images.

A CT image processing method replaces raw data channels with model values derived from a pre-scan to remove artifacts.

Top-view image processing estimates filling geometry to generate personalized marketing offers based on actual consumption states.

Extracting a self-gating signal from MRI pixel frequencies to detect periodically moving organs without external sensors.

A hierarchical segmentation method identifies first and second level airways within three dimensional voxel data to construct a complete airway tree.

Harmonic filtering extracts blood flow patterns at the heartbeat frequency, resolving contrast agent bolus blurring and noise in dynamic angiography.

Dynamic weighting factors adjust based on actual yields, resolving the trade-off between fixed model simplicity and deteriorating measurement precision.

Automated image processing replaces manual analysis to improve measurement precision and productivity for hydraulic fracturing planning.

An epsilon filter derives dispersion values across color components to suppress mosquito noise in compressed images.

A method estimates disparity values in occluded stereo image regions using blur and occlusion map data.

Superimpose extracted visible image data onto fluorescence images to display light output portions accurately.

Bilateral symmetry matching in body scanners isolates non-anatomical features, resolving low detection probability and high false alarm rates.

A migration system moves learning models between devices by verifying algorithm consistency and configuring parameters.

A windshield display apparatus projects obstacle images to the lower portion of the glass.

A remotely guided gun-fired round transmits live image data to a control platform for manual targeting.

Assigning color exclusively to a Bayer camera prevents artifacts caused by occlusion and enables accurate depth triangulation.

A defect inspection device determines image processing parameters from pre-stored exposure information to extract minute defect candidates.

A reslicing-based nonrigid registration method aligns radiological images using affine transforms and non-uniform resampling.

A specification function determines desired paths for medical objects using spatial and temporal control points.

Physical markers align digital models with device views, resolving location precision issues in augmented reality systems.

A video fidelity measure calculates pixel-wise differences between distorted and original pictures to assess quality.

Segmenting reference templates into sub-regions enables parallel processing that reduces tracking latency while maintaining detection accuracy.

A graph machine learning model analyzes disease lesions to predict patient survival and therapy response.

Segmented lookup tables and dithering reduce memory size and power consumption while maintaining color temperature uniformity.

Volume intensity projection images enable OCT data set alignment through landmark matching.

A method selects partial optical flow fields from segmented image regions to estimate relative movement and scale changes.

A camera processing system segments pixel intensity histograms to compress fog-affected pixels and stretch clear regions for improved contrast.

A radiation dosage monitoring system uses Cherenkov radiation detection and 3D surface modeling to estimate applied doses.

A scoliosis angle prediction method uses image segmentation to generate mask images for focused feature extraction.

Plug-in recognition modules resolve the contradiction between high-speed inspection accuracy and adaptability across diverse ordnance tasks.

A periodic noise pixel inpainting method uses non-periodic reference pixels to replace wiper artifacts in video frames.

Fast remapping of diffraction patterns to uniform spatial frequency grids enables coherent diffractive imaging at arbitrary angles.

A depth image processing method smooths trusted pixel values using time and content similarity weights across consecutive frames.

A machine learning model calculates dynamic segmentation parameters for target images to enhance processing precision.

An image processing apparatus extends the output range of brightness values for selected images to combine them with unselected images.

A medical image processing apparatus displays analysis results alongside input controls for doctor verification.

A segmented dental model alignment method copies surface elements from an old model into a current scan using bounding volume detection and minimum deviation positioning.

An image processing unit expands contrast data based on viewer position to align stacked display panels.

Iterative quasi-Monte Carlo sampling reduces computational time while maintaining image analysis accuracy.

QR code markers replace complex calibration objects to resolve the trade-off between measurement precision and device complexity in 3D reconstruction workflows.

A target image processing method adds compensation data to edge pixels based on pixel count values.

A scanning microscope calculates point spread functions using sub-Airy detector elements and blind deconvolution.

Aerial imagery extracts precise yaw angles and speeds, overcoming fixed sensor limitations to train connected automated vehicle models.

A virtual occluder positions within a capture volume to frame immersive content.

A convolutional neural network extracts local and global features to generate a bilateral grid matrix for image processing.

Deep learning analyzes visual and posture motion mismatch to quantify VR sickness, replacing subjective questionnaires with automated quantitative evaluation.

Unified network with shared weights handles large scene motion without separate pre-trained depth or flow networks.

Shadow analysis calculates occluded user positions, maintaining tracking continuity without extra sensors.

An image region designation device extracts partial regions near subject-void boundaries to optimize radiological image gradation.

Calculating a numerical order parameter from dermatoscopic images resolves subjective diagnosis by providing objective classification thresholds.

A circuit device with image analysis and distortion correction circuits manages backlight elements in head-up displays.

Automated frame of reference calibration replaces manual alignment procedures with optical tracking to resolve precision and time trade-offs.

A PET image reconstruction system segments coincident events by position to isolate true signals from scattering and random noise.

Infrared reflective paint renders road markings invisible to human drivers while providing high contrast signals for automated sensors.

A recurrent neural network selects pixels and color channels to identify vehicle environment features.

A processing system identifies hypointensive and hyperintensive portions in computed tomography image data to determine implanted lead orientation.