Xu et al., 2023 - Google Patents
Quaternion Quasi-Chebyshev Non-local Means for Color Image DenoisingXu et al., 2023
View PDF- Document ID
- 6077186362998161078
- Author
- Xu X
- Zhang Z
- Crabbe M
- Publication year
- Publication venue
- Chinese Journal of Electronics
External Links
Snippet
Quaternion non-local means (QNLM) denoising algorithm makes full use of high degree self- similarities inside images to suppress the noise, so the similarity metric plays a key role in its denoising performance. In this study, two improvements have been made for the QNLM: 1) …
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
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20172—Image enhancement details
- G06T2207/20182—Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
-
- 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
- G06K9/4604—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
- G06K9/4609—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections by matching or filtering
-
- 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
- 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
- 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
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
- G06K9/00268—Feature extraction; Face representation
- G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
-
- 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
- G06T5/001—Image restoration
- G06T5/002—Denoising; Smoothing
-
- 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
- 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
- G06K9/6201—Matching; Proximity measures
- G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
-
- 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
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
- G06T5/20—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image by the use of local operators
-
- 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
- G06T5/007—Dynamic range modification
- G06T5/008—Local, e.g. shadow enhancement
-
- 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
- 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
- G06K9/20—Image acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Xu et al. | Structure-texture aware network for low-light image enhancement | |
Hsu et al. | Single image dehazing using wavelet-based haze-lines and denoising | |
Muduli et al. | A novel technique for wall crack detection using image fusion | |
Pižurica | Image denoising algorithms: from wavelet shrinkage to nonlocal collaborative filtering | |
CN111681198A (en) | Morphological attribute filtering multimode fusion imaging method, system and medium | |
Malladi et al. | Image denoising using superpixel-based PCA | |
CN113724164B (en) | Visible light image noise removing method based on fusion reconstruction guidance filtering | |
Wang et al. | An efficient method for image dehazing | |
Jeon et al. | Low-light image enhancement using inverted image normalized by atmospheric light | |
CN114897741A (en) | Image blind deblurring method based on depth residual Fourier transform | |
Wang et al. | Single Underwater Image Enhancement Based on $ L_ {P} $-Norm Decomposition | |
Arulkumar et al. | Super resolution and demosaicing based self learning adaptive dictionary image denoising framework | |
Yuan et al. | Perona–malik model with a new diffusion coefficient for image denoising | |
CN117726537A (en) | SAR image denoising network method and system for self-adaptive multi-scale feature fusion AMFFD-Net | |
Yang et al. | CSDM: A cross-scale decomposition method for low-light image enhancement | |
Kang et al. | An adaptive fusion panoramic image mosaic algorithm based on circular LBP feature and HSV color system | |
Cheon et al. | A modified steering kernel filter for AWGN removal based on kernel similarity | |
Pu et al. | Fractional-order retinex for adaptive contrast enhancement of under-exposed traffic images | |
Lu et al. | DSPNet: Deep learning-enabled blind reduction of speckle noise | |
Xu et al. | Quaternion Quasi-Chebyshev Non-local Means for Color Image Denoising | |
Ning et al. | A non local feature-preserving strategy for image denoising | |
Sang et al. | Image enhancement based on skin-colour segmentation and smoothness | |
Zin et al. | Local image denoising using RAISR | |
Zhang et al. | Automatic genaration of sketch-like pencil drawing from image | |
Srigowri | Enhancing unpaired underwater images with cycle consistent network |