Chen et al., 2020 - Google Patents
Remote sensing image quality evaluation based on deep support value learning networksChen et al., 2020
- Document ID
- 16851736185663348767
- Author
- Chen G
- Pei Q
- Kamruzzaman M
- Publication year
- Publication venue
- Signal Processing: Image Communication
External Links
Snippet
Aiming at the problem that the remote sensing image quality evaluation models with manually extracted features lack robustness and generality, this paper proposes a 3D CNN- based architecture and nuclear power plant for accurate remote sensing image quality …
- 238000011156 evaluation 0 title abstract description 55
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20016—Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/40—Analysis of texture
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Chen et al. | Remote sensing image quality evaluation based on deep support value learning networks | |
CN113065558B (en) | Lightweight small target detection method combined with attention mechanism | |
CN112507997B (en) | Face super-resolution system based on multi-scale convolution and receptive field feature fusion | |
Kundu et al. | No-reference quality assessment of tone-mapped HDR pictures | |
CN111784602B (en) | Method for generating countermeasure network for image restoration | |
CN108230278B (en) | Image raindrop removing method based on generation countermeasure network | |
Fan et al. | Multiscale cross-connected dehazing network with scene depth fusion | |
Fan et al. | Multi-scale depth information fusion network for image dehazing | |
Yu et al. | Two-stage image decomposition and color regulator for low-light image enhancement | |
Huang et al. | SIDNet: a single image dedusting network with color cast correction | |
Liang et al. | Multi-scale hybrid attention graph convolution neural network for remote sensing images super-resolution | |
CN117237599A (en) | Image target detection method and device | |
CN116543433A (en) | Mask wearing detection method and device based on improved YOLOv7 model | |
Li et al. | An end-to-end system for unmanned aerial vehicle high-resolution remote sensing image haze removal algorithm using convolution neural network | |
Hu et al. | Hierarchical discrepancy learning for image restoration quality assessment | |
Shen et al. | Graph-Represented Distribution Similarity Index for Full-Reference Image Quality Assessment | |
Yuan et al. | Locally and multiply distorted image quality assessment via multi-stage CNNs | |
Yuan et al. | Single-image rain removal using deep residual network | |
Wang et al. | A novel singular value decomposition-based similarity measure method for non-local means denoising | |
Ahmadian et al. | Single image super-resolution with self-organization neural networks and image laplace gradient operator | |
CN117953310A (en) | Remote sensing multi-mode image classification method based on continuous scale feature network | |
Luo et al. | LCDA-Net: Efficient Image Dehazing with Contrast-Regularized and Dilated Attention | |
CN117671540A (en) | Method and system for detecting small target of attention aerial image based on multispectral frequency channel | |
Shi et al. | LCA-Net: A Context-Aware Light-Weight Network For Low-Illumination Image Enhancement | |
CN116993760A (en) | Gesture segmentation method, system, device and medium based on graph convolution and attention mechanism |