Dolhasz et al., 2016 - Google Patents
Measuring observer response to object-scene disparity in compositesDolhasz et al., 2016
- Document ID
- 4877152691946421114
- Author
- Dolhasz A
- Williams I
- Frutos-Pascual M
- Publication year
- Publication venue
- 2016 IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct)
External Links
Snippet
Image composites are combinations of image elements from different sources, often combined in a manner to give the appearance of a single, coherent image. This assesses the impact of low-level image feature offsets on observer response with respect to realism of …
- 230000004044 response 0 title abstract description 31
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
- 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
- G06T2207/30108—Industrial image inspection
-
- 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
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/50—Lighting effects
-
- 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
- G06T2200/00—Indexing scheme for image data processing or generation, in general
- G06T2200/24—Indexing scheme for image data processing or generation, in general involving graphical user interfaces [GUIs]
-
- 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
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/001—Texturing; Colouring; Generation of texture or colour
-
- 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
- G06T5/005—Retouching; Inpainting; Scratch removal
-
- 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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Liu et al. | Image defogging quality assessment: Real-world database and method | |
Duan et al. | Perceptual quality assessment of omnidirectional images | |
Čadík et al. | Evaluation of HDR tone mapping methods using essential perceptual attributes | |
Ma et al. | Objective quality assessment for color-to-gray image conversion | |
Yoshida et al. | Perceptual evaluation of tone mapping operators with real-world scenes | |
Xue et al. | Understanding and improving the realism of image composites | |
Yeganeh et al. | Objective quality assessment of tone-mapped images | |
Gijsenij et al. | Generalized gamut mapping using image derivative structures for color constancy | |
US8094964B2 (en) | Methods and systems for estimating illumination source characteristics from a single image | |
JP6786850B2 (en) | Image processing equipment, image processing methods, image processing systems and programs | |
Mittelstädt et al. | Methods for compensating contrast effects in information visualization | |
Krasula et al. | Preference of experience in image tone-mapping: Dataset and framework for objective measures comparison | |
Yang et al. | Underwater image enhancement using scene depth-based adaptive background light estimation and dark channel prior algorithms | |
Vazquez-Corral et al. | A fast image dehazing method that does not introduce color artifacts | |
US11576478B2 (en) | Method for simulating the rendering of a make-up product on a body area | |
Hulusic et al. | Perceived dynamic range of HDR images | |
Hashim et al. | No reference Image Quality Measure for Hazy Images. | |
Lecca et al. | An image contrast measure based on Retinex principles | |
Wong et al. | Comparative analysis of underwater image enhancement methods in different color spaces | |
Narwaria et al. | Effect of tone mapping operators on visual attention deployment | |
Dolhasz et al. | Measuring observer response to object-scene disparity in composites | |
Qureshi et al. | A comprehensive performance evaluation of objective quality metrics for contrast enhancement techniques | |
Piórkowski et al. | Automatic detection of game engine artifacts using full reference image quality metrics | |
Abebe et al. | Evaluating the color fidelity of itmos and hdr color appearance models | |
Patuano | Measuring naturalness and complexity using the fractal dimensions of landscape photographs |