Ding et al., 2020 - Google Patents
SIQA Based on 2D IQA Weighting StrategyDing et al., 2020
- Document ID
- 4941256572842908877
- Author
- Ding Y
- Sun G
- Publication year
- Publication venue
- Stereoscopic Image Quality Assessment
External Links
Snippet
As image quality assessment (IQA) methods for plant images have been explored thoroughly, some SIQA algorithms apply 2D IQA methods on both stereoscopic views independently and then combine the two scores to obtain an overall quality score by a …
- 238000001303 quality assessment method 0 abstract description 26
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
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- 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
- 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
- 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
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
- G06T2207/10012—Stereo images
-
- 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
- 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
- G06T7/00—Image analysis
- G06T7/40—Analysis of texture
-
- 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
-
- 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
- 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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Niu et al. | 2D and 3D image quality assessment: A survey of metrics and challenges | |
CN103250184B (en) | Depth Estimation Based on Global Motion | |
EP2560398B1 (en) | Method and apparatus for correcting errors in stereo images | |
Dong et al. | Human visual system-based saliency detection for high dynamic range content | |
US20150304630A1 (en) | Depth Map Generation from a Monoscopic Image Based on Combined Depth Cues | |
EP2293586A1 (en) | Method and system to transform stereo content | |
KR20110014067A (en) | Method and system for converting stereo content | |
Khan et al. | Estimating depth-salient edges and its application to stereoscopic image quality assessment | |
US8565513B2 (en) | Image processing method for providing depth information and image processing system using the same | |
CN108134937B (en) | A saliency detection method in compressed domain based on HEVC | |
CN107749066A (en) | A kind of multiple dimensioned space-time vision significance detection method based on region | |
CN114998596B (en) | Quality evaluation method of high dynamic range stereoscopic omnidirectional image based on visual perception | |
Sandić-Stanković et al. | Fast blind quality assessment of DIBR-synthesized video based on high-high wavelet subband | |
CN113038123A (en) | No-reference panoramic video quality evaluation method, system, terminal and medium | |
CN109510981B (en) | A Stereoscopic Image Comfort Level Prediction Method Based on Multi-scale DCT Transform | |
Jacobson et al. | Scale-aware saliency for application to frame rate upconversion | |
Li et al. | Blind stereoscopic image quality assessment using 3D saliency selected binocular perception and 3D convolutional neural network | |
CN114359955A (en) | Object visual field estimation method based on appearance features and space constraints | |
Poreddy et al. | BVRIQE: A completely blind no reference virtual reality image quality evaluator | |
Ding et al. | SIQA Based on 2D IQA Weighting Strategy | |
Zhou et al. | Reduced-reference quality assessment of DIBR-synthesized images based on multi-scale edge intensity similarity | |
Fan et al. | Blind stereopair quality assessment using statistics of monocular and binocular image structures | |
Iatsun et al. | A visual attention model for stereoscopic 3D images using monocular cues | |
Seitner et al. | Trifocal system for high-quality inter-camera mapping and virtual view synthesis | |
Kim et al. | Cnn-based blind quality prediction on stereoscopic images via patch to image feature pooling |