Image Enhancement TRIZ Cases

An information processing apparatus divides object areas based on Y-axis variations to estimate distances from a monocular camera.

A projector reduces irradiation beam coherence through temporal light-quantity modulation of the infrared source.

A computer aided diagnosis system groups successive image frames to classify regions of interest and combine results into a single output.

Movable patterned sheets separate diffuse and specular reflections, resolving multiple reflection errors in 3D shape reconstruction.

A gesture recognition system maps user pointing directions to real-world objects for accurate virtual object selection.

A locally adaptive segmentation method combines iterative region growing with morphological operations to extract vascular structures from 3D medical images.

An endoscope processor calculates diagnostic information from out-of-range oxygen saturation pixels to provide objective numerical indicators.

A machine learning model separates fixed architecture from dynamic data to enable rapid defect recognition on embedded wafer inspection systems.

A combined machine learning model analyzes pre-treatment DCE-MRI imagery to predict neo-adjuvant chemotherapy response in breast cancer patients.

A UAV records flight altitude and angle to segment image overlap regions for stitching, reducing onboard processing load.

Dynamic flash control adapts brightness using distance and illumination sensors to eliminate subject shadows while preventing overexposure.

A cell image evaluation device changes its assessment method based on captured image quality.

Hierarchical segmentation of MRI datasets into voxel integrity scores reduces computational resource consumption while maintaining predictive accuracy.

Channel pruning reduces model complexity and improves detection speed on resource-constrained devices while maintaining measurement precision.

Segmenting lung regions using airway extraction and Hessian matrix analysis improves lobe identification accuracy for surgical planning.

Convolutional neural networks generate pixel masks to identify translucent micro-objects against non-uniform backgrounds, improving detection accuracy.

A time-of-flight camera adjusts integration time and illumination intensity to capture depth images.

Image processing apparatus extracts position, time, and image data from multiple cameras to generate separate display screens for map, timeline, and video feeds.

Statistically combines color, edge, and motion cues into a saliency map for visual object detection.

A mammography system generates pre-scaled images by applying an overview breast window to each image in a series.

Variable Interscan Time Analysis decorrelates repeated B-scans to generate color-mapped images representing ocular blood flux and flow speed.

Segmented point illumination and focal stacking reduce lens flare artifacts while extending depth of field for high fidelity retinal imaging.

A lenticular display system detects user angles to present distinct content simultaneously.

A signal processing device extracts partial image data from compressed hyperspectral inputs to generate specific wavelength band images.

A controller adjusts the distance between two cameras to optimize image capture geometry.

Analyzing ambient light reflected from the eye detects refractive errors and astigmatism without active illumination.

Segmented element functions approximate track boundaries to resolve estimation errors and blurring in vehicle travel control.

Time-of-Flight cameras replace optical systems to measure container distances, resolving precision-reliability contradictions in varying weather.

A display panel divides image frames into partition pictures mapped to regions with varying sub-pixel densities.

An augmented reality system detects planes and captures poses to guide image acquisition.

A prediction model generates correction values for vehicle body panel molds using 2D depth maps derived from 3D design data.

A road surface inspection system captures images via stereo cameras and processes them using primary AI analysis for immediate data management.

Real-time optical detection of phase boundaries enables dynamic pump and rotor adjustments for consistent white blood cell separation.

Ultrasound imaging apparatus segments image data into anatomical regions and maps layered body markers to specific areas for clearer identification.

Morphological closing connects fragmented edges into contours for accurate sky segmentation without heavy computational costs.

Segmentation and preliminary action resolve overfitting in pulmonary embolism diagnosis by combining transfer learning with self-supervised feature extraction.

Dynamic FPGA reconfiguration matches circuit topology to specific robot work zones, enabling diverse image processing tasks within limited hardware constraints.

A mobile system automatically detects and masks photo backgrounds to generate compliant identification portraits without user intervention.

A Gaussian image quality analysis system computes pixel intensity changes to differentiate weak and strong pixels in vehicle camera feeds.

Optimizes HUD distortion function parameters to correct image quality without external equipment.

Minimizes differences between simulated and real statistical fingerprints to enhance photo-realistic image quality.

Automated borehole image analysis segments geological textures to identify formation facies, reducing manual interpretation time.

Transfer learning reduces training data needs while maintaining accuracy and lowering false positive rates in automated inspection.

Opposite readout gradient polarities acquire symmetric echo sets in one period, increasing acquisition efficiency and signal-to-noise ratio.

Segmenting display images by viewpoint allows selecting optimal visible light data per region, eliminating unnatural borders between multiple capture sources.

Segmenting the optical system into multiple independent chains simulates a large synthetic aperture, increasing light capture while reducing device weight.

A deep neural network system corrects image exposure errors using trained sub-networks and multi-level representations.

Automated inspection scenario generation selects optimal acquisition and classification parameters for wafer surfaces.

Laser-projected marks provide reference points that correct localization drift from wheel encoders and gyroscopes in indoor environments.

A photogrammetry device scans three-dimensional objects to calculate nominal surface contours for generating precise material removal and addition tool paths.

An image signal processor determines target kernel directionality to correct defective pixels using high-strength directional neighbors.

Selective coding based on object detection reduces bandwidth consumption while preserving image quality in video sequences.

Automated image analysis system processes multiple focal plane images to detect and classify biological analytes.

Segmenting whole-slide images into tiles reduces computational complexity while maintaining measurement precision for tumor biomarker assessment.