Image Enhancement TRIZ Cases

Computational projection of z-stacked images resolves out-of-focus regions to generate in-focus views of three-dimensional biological samples.

A method registers and aligns multiple eye images to identify in-focus regions using gradient analysis for high-resolution multifocal output.

A trained image segmentation model selects categories to discard based on recall rates before processing remaining objects.

Head-mounted displays register 3D patient models to reduce system complexity and improve alignment accuracy.

A sparse map construction system extracts road boundaries and object classifications from camera images to support vehicle navigation.

System uses explainable AI to resolve contradictions between diagnostic accuracy and time efficiency while reducing complexity.

A pipeline detection apparatus combines inertial navigation with camera imaging to calculate precise device positions during inspection runs.

Estimates foreground colors in border regions using alpha matte values and neighboring pixels to remove background contamination from composite images.

A measurement map configuration method selects target inspection marks to achieve comprehensive overlay accuracy.

Filtering correlated noise in the projection domain improves contrast-to-noise ratio and suppresses streak artifacts.

Matching 3D LiDAR lane data with camera images acquires coordinate conversion information, eliminating manual calibration steps.

Synchronizing spatial coordinates with ultrasonic echoes enables rapid three-dimensional heart model construction, reducing manual alignment time.

A video tracking system extracts scale and rotation invariant interest data points to initiate object detection in subsequent frames.

A segmentation system penalizes candidate features inside other mesh regions to prevent spatial overlap during adaptation.

Computes image feature values correlated with illumination conditions to select matching images from continuous captures.

A single laser line spans the device placement area and shoulder to detect position and orientation, resolving space constraints that prevent dual laser setups.

A contour extraction unit generates surface images from tomograms using brightness trains.

A controller projects 3D LiDAR data onto a circular grid map with adaptive cell sizes to cluster points efficiently.

A time-of-flight camera determines relative motion by correlating modulated reference signals with measurement signals from an object.

Multi-modality imaging reduces acquisition time by applying low-dose protocols to soft tissue while reserving high-dose scans for microcalcification detection.

Automated inspection system uses phase information of the image bearing member to accurately assess defect reproducibility despite positional variations.

A camera scanner projects operation instructions onto a stage and recognizes user gestures to adjust image acquisition.

Controller fuses radar and imager data to visualize projectile flight paths.

Defocused speckle patterns enable 3D motion estimation, resolving the trade-off between measurement precision and device complexity for micro-motions.

Predictive image processing narrows detection zones to reduce processing time while maintaining parking line accuracy.

Analyzing convex direction relative to deep regions suppresses false positives from shading effects near mucosal folds.

Combining per-layer image segments from multiple focal points resolves focus depth limits in charged-particle beam inspection.

An integrated image sensor captures color and infrared images simultaneously to detect object authenticity.

Integrated gaze point estimation apparatus combines neural network models with optical flow analysis to maintain accuracy during subject movement.

Fusing 2D disparity maps from multiband stereo cameras reduces computational overhead while maintaining depth estimation accuracy.

Processor adjusts mesh vertices to align 3D heart models with acquired images.

Motion vectors guide a deconvolution filter to reverse blur caused by object displacement during camera exposure.

A medical image processing apparatus aligns a primary spine scan with a reference image to label vertebrae.

Structured spray pixel sets tune random spray retinex parameters to fuse channels, reducing computational complexity while maintaining image definition.

Real-time classification identifies technical defects during chest radiograph capture, prompting immediate parameter adjustments and recaptures.

Dual subsets of intensity features resolve identification errors during object motion, ensuring accurate edge location determination.

A diagnostic apparatus combines manual and automatic tracing techniques to extract object tissue within a living body.

A processing system overlays virtual markings on fluoroscopic images using optical shape sensing data to enable distance and angle measurements.

A distractor mitigation system classifies people in images using salience and recognition cues to identify unwanted subjects.

A substrate processing monitoring apparatus adjusts video resolution and frame rates during execution.

Electronic device warps a 2D projection of a 3D mean-shape model to align landmark points with facial feature points in a color image.

Gaussian models classify pixels to separate foreground objects from background noise, reducing bandwidth consumption for high definition video transmission.

A camera mount uses image analysis to align its polar axis with celestial coordinates.

Segmenting images into tiles allows independent histogram modification with bias and plateau values, preventing noise artifacts while preserving shadow details.

Creating a contacts mask separates contact regions from step regions, enabling accurate line edge detection despite variable feature numbers.

Digital representation-based system generates image acquisition plans with waypoints, resolving manual inspection errors and high costs.

An image analysis device captures subject images while sensing its own inclination to adjust light emission and define a precise measurement region.

An image processing apparatus generates difference images to highlight bone and soft tissues from dual-energy radiographic data.

A processing system detects subject movement by matching captured image contours against stored direction information.

Segmenting volumetric video into depth-aware tiles allows rendering only visible regions, reducing computational load and bandwidth usage.

A correction value calculator adjusts block maximum and minimum values in compressed image data before decompression.

A test support device extracts changed symbols from monitoring system images and adds order information to guide verification.

A three-dimensional shape model matches extracted feature points from two-dimensional images to identify target object position and orientation.

A mobile device captures images of removable reference cards placed on a window to determine precise film dimensions.

Ultrasound image processing removes speckle noise by discriminating tissue edges from noise components, improving boundary identification accuracy.