Wei et al., 2018 - Google Patents
Medical image super-resolution by using multi-dictionary and random forestWei et al., 2018
- Document ID
- 5981611425573675872
- Author
- Wei S
- Zhou X
- Wu W
- Pu Q
- Wang Q
- Yang X
- Publication year
- Publication venue
- Sustainable Cities and Society
External Links
Snippet
Smart City has become the direction of the development of city. Telemedicine is an important part of Smart City. Telemedicine always provides clinical health care according to the medical images of the patient. High resolution images are expected for remote diagnosis …
- 238000007637 random forest analysis 0 title abstract description 58
Classifications
-
- 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
-
- 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
- G06T2207/30004—Biomedical image 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
- G06K9/36—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
- 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
- G06K9/6267—Classification techniques
-
- 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
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
- G06T3/40—Scaling the whole image or part thereof
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- 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
- 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
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Wei et al. | Medical image super-resolution by using multi-dictionary and random forest | |
Wang et al. | [Retracted] PSSPNN: PatchShuffle Stochastic Pooling Neural Network for an Explainable Diagnosis of COVID‐19 with Multiple‐Way Data Augmentation | |
Li et al. | An image fusion method based on sparse representation and sum modified-Laplacian in NSCT domain | |
Fang et al. | Spectral–spatial classification of hyperspectral images with a superpixel-based discriminative sparse model | |
Wu et al. | Learning-based super resolution using kernel partial least squares | |
Zhang et al. | Image super-resolution based on structure-modulated sparse representation | |
Xu et al. | Multi-exposure image fusion techniques: A comprehensive review | |
Wang et al. | Fast image upsampling via the displacement field | |
Chen et al. | A hierarchical spatiotemporal adaptive fusion model using one image pair | |
Lin et al. | Integrating model-and data-driven methods for synchronous adaptive multi-band image fusion | |
Vu et al. | Perception-enhanced image super-resolution via relativistic generative adversarial networks | |
Wang et al. | A group-based embedding learning and integration network for hyperspectral image super-resolution | |
Deshpande et al. | Super resolution and recognition of long range captured multi‐frame iris images | |
Dou et al. | Medical image super-resolution via minimum error regression model selection using random forest | |
Hu et al. | Single-image superresolution based on local regression and nonlocal self-similarity | |
Zeng et al. | Self-attention learning network for face super-resolution | |
Saeed et al. | A granular level feature extraction approach to construct hr image for forensic biometrics using small training dataset | |
Wang et al. | Image super-resolution using non-local Gaussian process regression | |
Zeng et al. | MG-CNFNet: A multiple grained channel normalized fusion networks for medical image deblurring | |
Yang et al. | Fast multisensor infrared image super-resolution scheme with multiple regression models | |
Wang et al. | A spatiotemporal satellite image fusion model with autoregressive error correction (AREC) | |
Cheng et al. | A new single image super-resolution method based on the infinite mixture model | |
Hidane et al. | Image zoom completion | |
Luo et al. | Piecewise linear regression-based single image super-resolution via Hadamard transform | |
Wang et al. | CD-GAN: A robust fusion-based generative adversarial network for unsupervised remote sensing change detection with heterogeneous sensors |