Image Enhancement TRIZ Cases

A machine learning system generates spatially varying maps to apply image processing functions at pixel-level strengths.

A neural network with shared parameter encoder branches processes image tiles in parallel to aggregate latent features.

Depth-based segmentation separates presenters from backgrounds, eliminating distracting visual noise in video feeds.

Image processing apparatus calculates feature amounts across hierarchical regions to generate accurate edge image data.

A medical image processing apparatus calculates feature values from pixel color tones to identify linear structures within living tissue images.

Single unpowered tool merges geometric patterns to calibrate visual, thermal, and range sensors simultaneously, eliminating separate checkerboard targets.

An image processing apparatus extracts pixels with low brightness variation across exposure conditions to set corresponding distance image pixels as non-imaging.

Signaling scaling offsets allows attribute decoding during geometry processing, reducing latency and memory footprint.

Internal camera compares guide member pattern images against reference data to detect deep insert skimmers and prevent unauthorized card data reading.

Pruning bounding boxes from labeled action-object videos to identify distinct object states for training datasets.

A video stream filtering method uses pixel color history to identify traffic light states and reduce false detections in driving assistance systems.

A user-hair-color model groups video pixels into skin, hair, and background sets to isolate foreground elements.

Segmenting images by frequency allows independent alignment of moving structures like the heart and vessels, reducing subtraction artifacts.

A pseudo-skeleton method enhances document text strokes by applying inverse-degradation functions to pixel values in difference areas.

A radiographic apparatus uses Fourier transform to detect moire pattern peak frequencies for line deficiency correction.

Pixel-specific row sums determine correction values that remove stripe artifacts from parallelized scanning images.

Virtual interventions calculate outcome maps for lead placement, resolving low therapy effectiveness in cardiac resynchronization procedures.

System merges multispectral imagery with LiDAR point clouds to detect equipment changes, reducing missed failures from limited manual inspection coverage.

Segmenting images into tiles reduces processing time and computational load while maintaining matching accuracy across large datasets.

A vehicle control apparatus calculates a target speed and performs deceleration control to match the desired speed at driving operation switching time points.

A camera parameter computation device calibrates orientation and height using road width information from conventional map data.

Processor divides target images into grid cells to classify feature points and estimate expanded planes for augmented reality environments.

A cross-sensor auto-calibration process aligns vehicle sensors using overlapping scene data from reference devices.

A learning-based shape model segments coronary artery structures from 3D computed tomography angiography images using landmark positions.

A flash band determination device detects artifacts by analyzing difference images while excluding high-luminance areas.

A tracking method supplements points below a threshold to maintain stability.

Pose alignment and single-layer feature extraction resolve the trade-off between classification accuracy and computational cost.

A video generation program synthesizes subject information with background areas in free viewpoint video based on tracked three-dimensional positions.

Segmenting target images by motion reliability allows selective compensation, reducing artifacts while lowering computational complexity.

Pre-computed normal maps replace real-time ray tracing to apply virtual lighting effects, reducing processing time while maintaining visual quality.

Non-linear chirp signals drive acousto-optic deflectors to track tissue movement, correcting motion artifacts in fluorescence measurements.

A machine learning system maps visual descriptors to depth information for real-time 3D estimation from single images.

Machine learning apparatus processes vector and raster data to generate ground-truth images and predicted polygons for automated map construction.

A passive vision system estimates height above ground level using optical flow and rigid flow analysis to generate dense depth maps.

An integrated GPU pipeline segments training and inference to reduce output delay from ten seconds to milliseconds.

A fiducial assembly enables automatic registration of surgical instruments to image data through x-ray projection processing.

An optical measurement system processes image frames to calculate a three-dimensional position vector, resolving occlusion issues during aerial vehicle landing.

An image analysis module captures probe unit images to automatically identify test positions on device under test surfaces.

Time code synchronization resolves complexity trade-offs in virtual camera systems, enabling seamless real-time view switching.

An information processing apparatus acquires character strings describing regions of interest to specify related areas and notify users.

Luminance-dependent saturation gains resolve banding and clipping artifacts during high dynamic range to standard dynamic range conversion.

A neural network system predicts 3D face parameters and generates a full UV texture map from a single input image.

Sorting filters extract a partial matrix to compute medians, reducing computation complexity while maintaining diagnostic image quality.

A method extracts specular reflection elements from images using chromaticity and brightness features to correct visual artifacts.

Dual-branch neural networks analyze UV and visible light images to detect surface defects in work pieces with consistent accuracy.

Dual depth sensors resolve low-resolution data into detailed 3D models, enabling accurate volume measurement without stopping industrial truck logistics.

CT imaging quantifies calcified regions to address stent crimping damage that reduces transcatheter heart valve durability.

Electronic device enhances images by adjusting parameters to resolve unclear characters, then isolates them through edge detection and outline correction.

A generative adversarial network trains using embedding differences to improve segmentation accuracy.

A dual-camera system captures bridge vibrations using a primary sensor and a secondary reference unit to correct motion errors from camera movement.

A diffusion model generates probability distributions for reservoir parameters using iterative noise removal from seismic images.

A tracking system predicts object location using stored image data to adjust sensor direction.

A video processing method classifies objects within a defined color space to apply masks for privacy protection.

Correlation algorithm links brain segment parameters to patient symptoms, resolving manual evaluation errors in neurodegenerative diagnosis.

A virtual video projection system synchronizes 3D animation with surveillance footage using matched camera parameters.

Shifting a diffractive optical element modifies the structured light pattern, resolving mechanical scanner speed and stability trade-offs.

Curved slice extraction aligns 3D tomographic images by generating 2D views at reference positions, resolving deformation alignment errors.

Paint dots track deformation to resolve accuracy limits around holes and irregular perimeters.

A vision system determines lane marker angles using side contrast values to extract straight and curved lines.

Continuous tracking of boards and hands enables gesture interactions that resolve overlay displacement and information overload.

An image processing apparatus partitions input images into pattern and texture regions to apply targeted quality enhancement algorithms.

A point cloud coder uses a neighbor information table to map Morton codes for attribute prediction.

A computer-aided analysis system identifies critical dermoscopy features using digital hair removal and watershed algorithms for image segmentation.

A spectral imaging system captures simultaneous spatial and wavelength data using optical splitting and dispersion mechanisms.

Intelligent ROI selection filters edge distortion in wide angle captures, enabling seamless transitions between narrow portraits and broad landscape views.

Single-device optical measurement reconstructs complete transverse wheel sections, eliminating complex track modifications and multi-stage procedures.

A graph plotting pixel counts against luminance levels and time positions to visualize HDR video data.

Segmented reflective members create asymmetric image distortion for parallax, resolving distance perception accuracy in vehicle electronic mirrors.

A computational system applies max-flow min-cut algorithms to cardiac meshes to identify optimized ablation targets.

Group control registers map virtual addresses to parameter registers, reducing command exchange time between processor and sensor.

Embeds road surface sensors to transmit overlap signals, resolving detection accuracy limits caused by restricted visual range.

A spatial-temporal image filter compensates for uncooled microbolometer thermal inertia, reducing motion blur and improving radiometric accuracy.

A computer aided diagnostic system segments lung tissue and aligns chest scans to measure pulmonary nodule volumes.

Separating illumination and reflectance components in borehole log data extends dynamic range and reduces ghosting artifacts.

Digital imaging captures encoded microparticle arrays to resolve scanning speed bottlenecks while enabling secure data transmission.

Combining interframe difference images creates composite training samples that resolve imbalanced datasets and improve multi-object motion detection accuracy.

A processor converts low-quality depth data into high-quality images for automatic user motion recognition.

Dynamic filter radius adjustment prevents over-blurring artifacts in ray-traced renders while anisotropic sizing elongates reflections under glancing angles.

Learned spectral priors mediate coded measurements to resolve spatial-spectral tradeoffs, reducing computational complexity.

A vehicle periphery monitoring apparatus displays detection frames around mobile objects only when their travel path requires driver attention.

Skeleton detection extracts keypoint data from live video streams to enable real-time pose recognition and background replacement on mobile devices.

Double-second-order regression diagnosis models exclude outliers to improve background fitting accuracy for uneven brightness areas.

A vehicle image processing device determines vanishing point height using virtual lines or road region segmentation based on estimated distance.

A microfluidic digestion system integrates an internal camera and computing device to track tissue sample changes during enzymatic processing.

Image processor recognizes balloon expansion through pixel value changes to display treated areas, eliminating manual pre-post image comparison.

Combining chromatic aberration, wavelet energy ratios, and Chebyshev moments separates in-focus images from out-of-focus ones despite single-image constraints.

Segmented image processing applies distinct correction parameters to specific body regions, resolving distortion in natural proportions without uniform scaling.

Blendshape regularization reduces tracking noise and improves animation realism during retargeting.

An integrated machining workstation combines a projector and photogrammetry device to determine workpiece pose and project instructions at a single station.

Segmented modules and parameter adjustments resolve accuracy versus environmental adaptability trade-offs for assisted driving.

Machine learning component reduces noise via feedback loops, avoiding manual ISP tuning.

Dual scalers optimize content scaling by adjusting magnification based on output resolution, reducing data rates and power consumption.

A region-based image processing apparatus calculates distinct blur kernels for divided shot image areas to generate natural depth-of-field effects.

An automated image segmentation method identifies regions of interest in nuclear medicine scans to determine cardiac structure axes.

A noise simulator generates synthetic training data pairs to overcome limited real medical image availability, improving deep learning denoising performance.

Kernel-based transformations and quadrilateral scoring detect document boundaries in occluded images, resolving accuracy issues from irregular edges.

A ground point segmentation algorithm computes a piece-wise local representation using maximum height map filtering.

Local statistical parameters quantify echo texture features, reducing inter-observer variability in thyroid tumor diagnosis.