Image Enhancement TRIZ Cases

An image processing apparatus extracts object regions by integrating pixel values from multiple initial extraction results.

Real-time slice status display prevents redundant evaluation and ensures complete diagnostic assessment of three-dimensional breast tomosynthesis datasets.

Doppler-constrained scan matching aligns point clouds to estimate vehicle heading, resolving the trade-off between measurement accuracy and processing time.

A computer method isolates edge pixels and computes local contrast to sharpen degraded document images.

Bins defects using combined optical attributes to target electron beam review, reducing time while maintaining classification purity.

Complementary image enhancement resolves calibration errors and pixel mismatches in stereo camera modules to produce accurate depth information.

Automated detection of image skew and contaminants generates a visual representation with indicia, eliminating manual hard copy review.

Speckle patterns guide fringe matching in handheld scanners, eliminating mark point splicing and improving accuracy.

Deep convolutional neural networks generate professionalism scores that drive discrete variable optimization for automatic image cropping.

MASHA system extracts brain circuit patterns from task-based fMRI data using automated hierarchical searching.

A data feature augmentation network generates synthetic occlusion features to train detection models with minimal annotated samples.

Dynamic decomposition levels tailor processing to human visual sensitivity, reducing computational complexity while maintaining measurement precision.

An iterative method expands spectral images and detects subpixels using constrained energy minimization.

A dynamic biomedical graph segregates diverse inputs into manageable groups to clarify decision paths in medical diagnostics.

A stereo camera system uses disparity maps to detect rectification errors in parallelized image streams.

Applying gain and development processing to individual images before composition prevents noise amplification and preserves edge sharpness.

A method projects grouped 3D point cloud data onto predetermined planes to generate packed 2D images for efficient encoding.

An infrared camera captures intensity values to compute depth images based on light falloff principles.

A transportable CT scanner acquires image data and processes transformation matrices to map patient anatomy into the treatment device coordinate system.

A vehicle imaging system transforms overlapping camera feeds into a 3D model for seamless projection.

Convolutional neural networks analyze film images to detect defects, replacing manual inspection that suffers from low accuracy and high time consumption.

A controller cooperates with a smart camera to execute inspection processing on transferred images.

Encoder signals object motion parameters to decoder, generating intermediate pictures that smooth mouse pointer movement at low frame rates.

PFNet segments camouflaged objects by mining distraction information, resolving background similarity that degrades detection accuracy.

A self-supervised method splits digital histopathology images into tiles and generates similarity labels based on spatial proximity to train machine learning models.

Automated PET-MRI registration calculates lateralization indexes to localize epileptogenic foci.

Selective laser energy adjustment compensates for ghosting on photoconductive surfaces, extending component life and reducing print costs.

Augmented reality display apparatus superimposes tidal current symbols on vessel camera feeds using external sensor data.

Magnetic resonance imaging apparatus acquires cerebrospinal fluid signals at multiple time phases during oxygen inhalation.

Circuitry rotates wide-angle images around a vertical axis to correct orientation before converting them into cube map format.

Automated image outlining extracts tool traces from crime scene evidence, resolving the loss of three-dimensional information in two-dimensional impact marks.

Automated image processing system captures and analyzes coin surface contours to identify type and value.

A 3D image reconstruction method segments initial depth data to detect local planes and applies edge-preserving smoothing for realistic visual output.

GNSS-equipped vehicles with identification markers serve as moving ground control points for aerial photogrammetry.

Segmenting point cloud geometry and attributes into independent video streams reduces encoding complexity while maintaining high service quality.

A deep integration network fuses appearance and motion tracking positions to derive accurate target coordinates.

Spatially-implemented super-resolution restores pixel detail in enlarged center regions of rearview images, countering resolution loss from optical stretching.

Sub-wavelength meta-structure layer replaces bulky optics, reducing volume while maintaining precision for augmented reality systems.

A detection unit emits light on a recording medium to calculate width based on reflected intensity thresholds.

A computer-implemented method extracts scatter plot data points by analyzing pixel sets and generating templates for automated identification.

A stereoscopic deep neural network uses semi-supervised training with LIDAR and photometric data to estimate depth.

A two-stage neural network system classifies compartments using 3D CT imaging and performs image segmentation to identify hazardous objects.

A calibration unit establishes coordinate relationships to stitch non-overlapping images into a single composite view.

Segmenting event camera fields of view into regions of interest prevents motion outside the target area from degrading textural image quality.

A composite display unit projects morbid portions from designated ophthalmic layers onto a single two-dimensional image.

Processing circuit extracts disease data from executed scan protocols to control subsequent imaging steps.

A surgical device applies conditional operational restrictions based on medical information received from an independent second system.

Autonomous vehicle sensors calibrate using a hovering unmanned aerial vehicle carrying a checkerboard to capture multi-angle images.

A camera and controller system captures health monitor displays in operating rooms without wired connections.

Parallel fuzzy convolutional neural networks classify retinal images using ensemble learning to resolve sample scarcity and distribution differences.

A pixel defect detection circuit updates confidence values for defective pixels using flat region analysis.

Baseline CT radiomic feature extraction predicts pemetrexed response in non-small cell lung cancer, reducing unnecessary chemotherapy administration.

A harvester display system generates a graph of grain processing quality values over time for operator monitoring.

A rotating filter switches between green and blue narrow band illumination to capture distinct image signals for composite processing.

Fourier transform clustering on TEM partial regions determines crystallinity without labeled data, resolving precision limits of brightness-based evaluation.

Hydrogen density mapping calculates stopping power ratios to reduce range uncertainties and improve Bragg peak placement accuracy.

A rotationally asymmetric filter corrects asymmetrical blurs from optical systems, reducing undershoot and overcorrection in specific directions.

A monocular camera system estimates focal length and principal point through self-calibration to compute 3D positions of semantic landmarks.

Deformable mirrors provide field-dependent and spectral compensation for optical aberrations, reducing device complexity.

Virtual twins generate baselines to estimate long range trajectories, avoiding deception by similar shapes.

Automated video clipping system uses object detection models to isolate human body regions, resolving manual labor bottlenecks in vertical video production.

Convert high-cardinality categorical data into image formats to resolve efficiency and reliability bottlenecks in predictive analysis.

Antennas arranged at different vertical locations transmit radio waves to read RFID tags from commodities placed on a worktable.

Segmented oblique and coaxial illumination paths reduce stray light interference, enhancing crack detection sensitivity and measurement accuracy.

An image correction device applies excessive emphasis to luminance gradation and color tone parameters.

A mammography controller adjusts compression plate pressure and rate based on patient systolic and diastolic blood pressure measurements.

Computational modeling maps navigation electrodes to ablating surfaces, resolving discrepancies between electrode positions and actual tissue geometry.

Automated thermal imaging replaces manual checks to detect incontinence events, reducing caregiver labor costs while maintaining patient safety.

A display apparatus limits graphic overlay brightness to enhance visibility.

Image capture devices detect physical whiteboard content to generate virtual interfaces, enabling remote users to contribute without complex setup.

Segmenting objects into distinct parts via a spanning tree improves detection precision while managing computational complexity in moving vehicle environments.

A device derives absolute scale depth information from captured images using geometrical consistency across multiple time points.

Segmented neural networks resolve resolution-quality trade-offs by generating specific features like mouths and teeth without visible seams.

A convolutional neural network generates eddy current correction masks for medical imaging scans.

A machine learning model generates a mask for the speech portion of a person's image to synthesize natural moving images.

Fusing head key feature point clouds into target object models reduces production time and cost while maintaining manufacturing precision.

A Reeb graph structure represents lesion shapes using isolation measures, resolving limited descriptive power of scalar features.

A method divides video streams into portions to set motion trigger levels based on bitrate statistics.

An automated diagnosis model processes immunohistochemical images using contrast enhancement and U-Net neural networks for precise identification.

A display panel brightness compensation method corrects regional luminance using photographing component data and preset grayscale images.

Dynamic anisotropic diffusion filtering preserves scene discontinuities and improves resolution by selectively removing speckle noise from SAR data.

Dynamic holographic scanning detects 1-50 μm Pt-derived defects without mechanical tensioning, preventing breakage during bending.

Machine learning module detects waste objects in collection vehicle hoppers using optical sensors and image classification.

An imaging device captures non-imaging patient vitals through a dedicated communication interface to merge physiological data with image streams.

Automated image analysis of visual markers determines precise ophthalmic fit measurements, eliminating the need for physical retail establishment visits.

Mobile devices achieve precise color shade differentiation by calculating specular and diffuse light fractions alongside parallax-based range measurements.

Storing infrared and depth templates in a trusted execution environment prevents template theft and tampering that compromises standard face image verification.

Eye gaze detection circuitry cross-references automated ischemia findings with clinical symptoms to resolve diagnostic ambiguity in non-contrast CT scans.

Sequential monochromatic imaging under distinct light classes preserves image resolution while reducing data volume for underwater surveys.

A video processing method segments streams by tracking entity timestamps and confidence scores across frames.

Adjusts image saturation components based on extracted luminance values to enhance color quality without amplifying visual artifacts.

A sensor with multiple photodiodes captures images at varied focus positions to extract wavefront data.

A photoacoustic image evaluation apparatus registers pre- and post-treatment images to extract blood vessel regions.

A hierarchical image processing unit manages display regions by adjusting surface area and position based on virtual viewpoint movement.

A template matching apparatus computes multiple similarity degrees using characteristic amounts and residual calculations to specify positions accurately.

A dual-stage detection method identifies black borders in video frames using grayscale and edge image analysis.

A VR image processing method segments frames using pose change thresholds to reduce rendering data volume.

A medical image synthesis system displays overlapped X-ray regions alongside accuracy indicators to verify overlap quality.