Automatic Image Splicing Detection Based on Noise Density Analysis in Raw Images.
Thibault JulliandVincent NozickHugues TalbotPublished in: ACIVS (2016)
Keyphrases
- input image
- image data
- high contrast
- image analysis
- image noise
- image features
- image collections
- test images
- image structure
- image degradation
- image classification
- spot detection
- image retrieval
- background noise
- low signal to noise ratio
- intensity variations
- imaging process
- edge detection
- image pixels
- original images
- gaussian noise
- image regions
- noise sensitivity
- image set
- image edges
- geometric distortions
- image content
- region of interest
- pixel values
- segmentation algorithm
- segmentation method
- lighting conditions
- degraded images
- intensity distribution
- imaging devices
- bounding box
- low light
- image database
- image matching
- denoising methods
- image quality
- multiscale
- keypoints
- single image
- pixel intensities
- spatial coordinates
- image statistics
- image segmentation
- intensity gradient
- distorted images
- pavement distress
- complex background
- image restoration
- image registration
- noise free
- speckle noise
- feature points
- scale space
- removing noise
- texture and shape features
- low contrast
- contrast enhancement
- noise level
- partial occlusion
- object detection
- noise free image
- face recognition