Image Enhancement TRIZ Cases

A polarization imaging apparatus generates normal candidate information per pixel to calculate plane orientation using zenith and azimuth angles.

An image processing system uses a calibration plate to calculate color correction values for accurate commodity recognition.

A unified neural network model combines data from multiple datasets with different label spaces to generate a single classification output.

Generates workspace volumes for surgical instruments and references them to image capture frames, defining reachable areas within captured data.

A medical image processing apparatus applies user-defined enhancement curves to band pass images for improved structure visibility.

Cluster analysis algorithm extracts signal series from image areas, reducing data volume and computational effort while identifying weak analyte signals.

A three-dimensional sensor measures chip surface height to determine precise focusing positions for image sensors during tray inspection.

Predicting defects via AI models and generating process maps eliminates time-consuming manual inspection and simulation loops in additive manufacturing.

A tunable acoustic gradient index lens modulates focus position to correct longitudinal chromatic aberration in imaging systems.

Real-time imaging captures environmental control system components for automated visual analysis, detecting malfunctions without intrusive sensors.

Image processing device integrates pixel brightness to identify candidate locations, reducing false detection caused by non-uniform illumination in vehicles.

A smart tolling system stitches vehicle trajectories across multiple video streams to synthesize complete profiles from fragmented detection data.

A sensor system expands coordinate information values to obscure pixel data patterns during asynchronous transmission.

Segmented standard and sorting regions resolve the contradiction between candidate search capability and positioning accuracy in visual inspection.

Lowering white luminance creates an extended range above the white point, enabling saturation enhancement while maintaining standard display compatibility.

A defect inspection device uses a mask position setting unit to identify common regions across segmented unit areas for accurate signal comparison.

An AI model estimates missing image data to adapt processing chains, reducing radiologist reading time caused by inconsistent X-ray system flavors.

UV mapping grids rectify 3-D perspective distortions in primary images, enabling accurate Optical Character Recognition on complex geometries.

A deep neural network adjusts pictorial depth cues like blur and contrast without relying on inaccurate depth maps, preventing incorrect depth information.

A projection display calibration method selects reference feature points to detect camera position deviations.

Fitting non-linear curves to edge points resolves measurement inaccuracies for complex shapes in advanced semiconductor manufacturing.

Extracting monochrome signals from color pixel groups calculates depth from blur differences, reducing axial chromatic aberration errors.

Chroma filtering on clear pixel data reduces noise amplification during color correction, improving the signal-to-noise ratio.

Candidate image signal processors process original images for perception task models to select optimal configurations.

A processor matches 2D images with 3D pose data to extract accurate head rotation and position information.

Automatic zone labeling system overlays procedurally-defined anatomical regions onto real-time ultrasound volumes.

Aligning high-frame-rate visual tracks with low-cost infrared thermal detections reduces false positives while maintaining accurate indoor person tracking.

Segmenting the environment into predefined sections reduces data processing complexity while maintaining localization precision for automated driving.

A controllable inspection vehicle captures structural images to generate 3D models for automated claim processing.

A depth optimization method partitions maps into planes and fills holes using segmentation maps to generate accurate 3D data.

Segmenting foreground, middleground, and background layers reduces image distortion and cracking during single-viewpoint conversion.

A fully automated system segments head-neck arteries in medical images using anatomical landmarks and seed identification.

A light field camera array controller detects view inconsistencies between overlapping cameras and generates correction data to maintain immersive depth cues.

Labeling device adds dummy regions to break privacy label correlations, enabling correct network operation on original images.

A depth detection apparatus computes multiple depth maps from raw time-of-flight sensor frames using dynamic measurement patterns.

Replacing bulky optical markers with magnetic sensors eliminates occlusion and breakage while improving hand movement detection accuracy.

A background modifier segments captured image pixels into foreground and background sets using spatial coordinates to replace the background with template pixels.

Automated landmark matching aligns multiple medical scans to eliminate manual alignment time while enabling precise tracking of anatomical changes.

Radiation treatment planning system registers images to determine dose values for voxels.

Navigation apparatus renders virtual endoscopic views of guide wire position within volumetric medical imaging data.

A tomographic imaging method corrects source positioning errors using reference image transformations to improve image quality.

A neural network model reconstructs magnetic resonance images from partial k-space data to reduce truncation artifacts.

A downhole imaging system applies temperature-based distortion data to captured images for accurate 360-degree views.

A dynamic image object system generates synthetic images from source data to enable personalized viewing experiences.

A deep convolutional neural network generates professionalism scores to drive automatic image cropping and rotation.

Pixel digital frame masks determine frame sequence numbers to evaluate cloud gaming fluency despite image noise and complexity.

Automated screenshot analysis extracts error text via machine learning segmentation, resolving communication gaps and reducing support team resolution time.

Segmenting images into regions allows applying distinct fog removal parameters to improve object visibility while preserving natural appearance in clear areas.

Dual beam splitters and a retroreflector merge light paths from segmented display halves, eliminating the screen-door effect in virtual reality headsets.