Image Enhancement TRIZ Cases

An extendable, actuator-controlled camera inspects EUV source interiors without manual chamber entry or protective-gear discomfort.

A server analyzes received images and generates processing code, reducing interaction steps for web-based manipulation and sharing.

This collaborative tool compares annotations with expert or model references, then targets training with attention maps.

This case projects 3D coordinates into spherical range images, adds semantic and lane data, and supports efficient location recognition.

A hierarchical encoder-decoder uses paired spatial and channel attention to reduce self-attention complexity from quadratic to linear.

QR-enabled registration supports computer component repair, upgrades, and resale.

Synchronized imaging links contact images to displacement data, exposing abnormal waveform causes.

This case uses multiple cameras to select a tracker and share target distance, supporting accurate surveillance without alerting the target.

A variational autoencoder reconstructs 3D CT images from 2D micro-resistivity scans to identify rock crack location and shape.

The case automates synthetic training-image generation from compact object data for markerless pose estimation with less manual effort.

Virtual instruments replace printed collateral to reduce errors in negotiation training.

Phase-difference distributions replace nonlinear approximation with statistics for simpler, more reliable MRI target-material evaluation.

This case uses denoising, edge detection, and region-based disparity maps to improve optical flow precision and speed.

Disparity maps and segmentation automate aerial object detection and classification.

Enlarging shifted shots before difference calculation improves moving-region detection and produces more natural composite images.

A multi-color skin calibrator normalizes feature colors and geometry despite changing illumination and image-capture conditions.

This case combines volumetric fusion, illumination estimation, and multiview SfS to refine normals and albedo from noisy depth frames.

The system compares scan images over time to alert users to worsening image abnormalities and support planned maintenance.

Automated MRI segmentation tracks the aortic arch centerline and generates reproducible 3D measurements for aneurysm surveillance.

This inspection system uses camera positions and AI object detection to sequence relevant live views into a coherent route.

Images captured at the heart’s pulsation interval are aligned to reduce device-position drift during angiographic procedures.

This remote monitoring case combines breathalyzer testing, facial checks, video, and GPS alerts for reliable sobriety verification.

Fully synthetic training and adjustable disparity ranges help one learned stereo architecture support diverse camera baselines.

This case combines phased-array haptics with acoustic and optical sensing for fast, accurate tracking without disrupting feedback.

A server combines sensor data from multiple vehicles to locate damaged road areas and prioritize repair resources.

The case segments person detection, distance calculation, and risk generation to assess infection risk in target regions.

A trained feature model maps defect images to representative points, revealing classification similarity and new defect types.

This case combines lightweight neural networks with surfel fusion to build semantic indoor 3D models in real time on mobile devices.

This model eye uses flexible, pathology-printed retinal layers and clouded lenses to support realistic imaging evaluation and training.

Machine learning compares predicted and actual movement routes to identify suspicious persons and reduce operator video review.

Loss-function minimization turns multi-pose 2D C-arm X-rays into usable 3D structures for more accurate tool localization.

A camera locates beacon pixels and decodes blank frames, enabling programmable data transmission without expensive detection hardware.

This case links CT images with body position images so external viewers can identify scan posture and imaging mode.

Location identifiers map interleaved image color data, helping devices process multiple formats without costly conversion.

This case lifts 2D joint points to 3D and uses projection relationships to estimate camera position without fixed references.

Separate prompt and processing modules train multiple image tasks while targeted parameter updates improve prediction accuracy.

This case combines multi-scale segmentation and deformation-field training to align MRI and ultrasound images with less overfitting.

Multi-image OGI processing colors motion by direction and speed, then removes camera movement to reveal gas plumes.

This case removes albedo prediction to soften shadows and reduce specular highlights on mobile devices with lower compute demand.

Distant cameras reduce tracking precision; common coordinates improve object fusion.

The controller limits histogram data to the optical image area, avoiding false low-luminance peaks during exposure adjustment.

Anomaly masks turn positive images into forged negative samples, reducing manual labeling and overfitting in scarce-data training.

This case combines passthrough vertex adjustment with predictive time-warping to improve perspective sync and reduce motion sickness.

This case matches player locations to footpoints, repairs limb errors, filters spectators, and projects poses into 3D play areas.

This case uses distortion factors and image processing to correct stereoscopic surgical viewer images, reducing optical complexity and cost.

Sequence-adaptive tissue segmentation and transformation matrices align multimodal brain scans despite lesions and intensity differences.

Diagnose image-forming units from printed images without test charts.

Feature-vector matching identifies checkout items from camera images, reducing manual scans, wait times, and cashier intervention.

A second display mirrors figure movement with indicators, helping users recognize projected-image changes beyond the projection target.

Pre-shot scene images identify the current background and replace it digitally, avoiding costly projection screens, TVs, and green screens.