No-reference quality assessment using natural scene statistics: JPEG2000

Measurement of image or video quality is crucial for many image-processing algorithms, such as acquisition, compression, restoration, enhancement, and reproduction. Traditionally, image quality assessment (QA) algorithms interpret image quality as similarity with a "reference" or "per...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE transactions on image processing Ročník 14; číslo 11; s. 1918 - 1927
Hlavní autoři: Sheikh, H.R., Bovik, A.C., Cormack, L.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York, NY IEEE 01.11.2005
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Applied sciences
Blind quality assessment (QA)
Computer Simulation
Detection, estimation, filtering, equalization, prediction
Distortion measurement
Exact sciences and technology
Humans
Image coding
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image processing
image QA
Image quality
Image restoration
Information Storage and Retrieval - methods
Information, signal and communications theory
JPEG2000
Layout
Models, Statistical
natural scene statistics (NSS)
no reference (NR) image QA
Quality assessment
Quality Control
Signal and communications theory
Signal processing
Signal Processing, Computer-Assisted
Signal, noise
Statistics
Subtraction Technique
Telecommunications and information theory
Transform coding
Video compression
Video Recording - methods
Video coding
JPEG2000
Blocking artifact
Similarity
Image processing
Data compression
Image compression
Algorithm
Blurred image
Subjective evaluation
Video signal processing
natural scene statistics (NSS)
Image quality
no reference (NR) image QA
Image coding
Wavelet transformation
Quality control
image QA
Signal processing
Blind quality assessment (QA)
Image evaluation
ISSN:1057-7149, 1941-0042
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Measurement of image or video quality is crucial for many image-processing algorithms, such as acquisition, compression, restoration, enhancement, and reproduction. Traditionally, image quality assessment (QA) algorithms interpret image quality as similarity with a "reference" or "perfect" image. The obvious limitation of this approach is that the reference image or video may not be available to the QA algorithm. The field of blind, or no-reference, QA, in which image quality is predicted without the reference image or video, has been largely unexplored, with algorithms focussing mostly on measuring the blocking artifacts. Emerging image and video compression technologies can avoid the dreaded blocking artifact by using various mechanisms, but they introduce other types of distortions, specifically blurring and ringing. In this paper, we propose to use natural scene statistics (NSS) to blindly measure the quality of images compressed by JPEG2000 (or any other wavelet based) image coder. We claim that natural scenes contain nonlinear dependencies that are disturbed by the compression process, and that this disturbance can be quantified and related to human perceptions of quality. We train and test our algorithm with data from human subjects, and show that reasonably comprehensive NSS models can help us in making blind, but accurate, predictions of quality. Our algorithm performs close to the limit imposed on useful prediction by the variability between human subjects.
Bibliografie:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
content type line 23
ObjectType-Undefined-1
ObjectType-Feature-3
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2005.854492