Image Enhancement TRIZ Cases

A gradient direction calculation device uses integer arithmetic and quadrant determination to process pixel data efficiently.

Segmenting classification into dedicated networks improves image retrieval precision while managing device complexity.

A load estimation apparatus uses body-mounted sensors to calculate posture loads based on motion patterns.

A two-stage depth estimation framework uses a spherical warping layer to generate high-quality omnidirectional depth maps from monocular inputs.

Feature map-based motion estimation generates four-dimensional motion fields to correct respiratory and cardiac artifacts in computed tomography.

A normalization parameter adjusts division operations to enhance image deformation accuracy.

A deep neural network detects objects to generate weighted image values that update sensor parameters.

A flexible stereo depth correction method estimates pitch-roll and yaw biases using visual-inertial odometry features to rectify misaligned images.

Local feature attention mechanism captures and combines pedestrian feature sequences to improve identification accuracy across varying postures and distances.

System minimizes radius-to-axis distance differences during bundle adjustment to suppress scale-drifting errors in pipe inspection.

Pre-computed optical property lookup tables eliminate real-time simulations, reducing measurement time while maintaining precision.

Computational stitching joins component image frames from multiple cameras to generate panoramic video productions automatically.

Progressively upsampling label maps through an energy function fills missing portions and boosts resolution without excessive computational complexity.

Imaging controller detects support surface edges using Hough lines and depth segmentation to resolve accuracy issues from varying lighting and object positions.

Attribute class labels replace precise manual annotations to reduce training data requirements while maintaining detection accuracy.

Mobile device SLAM 3D bounding boxes guide deep neural networks to identify products, eliminating manual labor and inventory delays.

A coded-exposure camera system modulates temporal parameters to preserve high spatial frequencies in moving objects.

A light-field microscope maps three-dimensional sample volumes onto two-dimensional sensor arrays to extract ballistic signal components.

Grouping identical kernel coefficients reduces multiplier count and storage space, resolving hardware complexity in image processing.

A video processing method calculates current and historical effect key points to generate natural visual trajectories.

Embeds invisible indicia into photographs to automatically obscure facial features on social networks.

A rear-view image display device adjusts the view-angle value based on detected vehicle distance to match displayed object sizes with mirror reflections.

Sparse depth point extraction reduces transmission load while maintaining rendering accuracy for extended reality head pose alignment.

Mutual feature quantities calculate a discrimination boundary surface to resolve large apparent image discrepancies in semiconductor wafer inspection.

A machine learning generator network fills broken lane data using adversarial training to restore accurate geometric continuity for autonomous navigation.

A graph convolutional neural network extracts features from spherical graph signals to generate accurate 360-degree saliency maps.

A dental CT imaging system applies sharpening filters only to non-artifact regions to enhance image clarity.

A tailored training dataset improves object detection accuracy by removing redundant video frames from the model input.

An automated image processing framework replaces manual measurement of irregular follicles, improving ART timing accuracy.

Alternating display periods with a polarization switch prevents real-world light addition and reduces mask blur in augmented reality systems.

Image processing unit tracks cervical tissue landmarks to compensate for camera movement and tissue deformation, ensuring precise treatment area localization.

Clustering pixel value changes divides perfusion images into regions, enabling accurate registration despite contrasting anatomical structures.

A medical image processing apparatus registers neural activity data with blood vessel images to guide electrode stent positioning.

Local color statistics guide deconvolution to decouple edge sharpness from strength, reducing ringing artifacts and over-smoothing.

An image processing apparatus acquires camera images from multiple facility cameras to identify surveillance targets.

A shape measurement device divides the imaging plane into multiple regions to select an image obtaining region based on designated requirements.

Action-guidance functions predict defect progression over time, eliminating manual labeling constraints while maintaining detection accuracy.

A multispectral display device reconstructs subcutaneous structures using wavelength-specific imaging and anatomical model matching.

A fire detection system uses optical flow and image feature modules to identify candidate areas in input images.

A booster engine enhances frame sequences by collaborating with a first stage circuit to adjust quality degradation.

A simulation system generates realistic images using computer graphics to replicate severe weather conditions.

A shape similarity metric calculates union and intersection differences to compare geometric forms.

A hybrid system segments lesions using handcrafted color and vessel models before deep learning classification.

A fault detection module analyzes cross covariance and edge presence in camera images to identify component degradation.

A transparency setting unit adjusts edge regions of object images to reduce overlapping color components in tandem printing.

A dual mechanical stage system moves a wafer at constant velocity while a lighter secondary stage adjusts position to maintain optics alignment.

Automated optical inspection replaces manual testing to evaluate spot weld integrity in real time, eliminating rework and ensuring 100% quality coverage.

Object detection algorithms identify beverage containers in digital images to estimate quantities, resolving manual sorting bottlenecks in opaque receptacles.

An automated system extracts features from submitted print jobs to generate proposed enhancement operations for digital printing workflows.