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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Patil, M. Paturkar, A. |
| Copyright Year | 2015 |
| Description | Author affiliation: Dept. of Electron. & Tele-Commun., Savitribai Phule Pune Univ., Pune, India (Patil, M.; Paturkar, A.) |
| Abstract | The quality of measuring the image is a complicated and difficult process since humans opinion score is affected by physical and psychological factors. Several techniques are proposed for measuring the image quality but any of this techniques is considered to be ideal for measuring the image quality. Image quality assessment plays a significant role in the field of image processing. Image quality assessment (IQA) estimates the quality of an image by measuring the difference between the reference and distorted images. Distortion estimation in objective domain also plays a significant role during IQA. There are three categories of IQA methods: full-reference (FR), partial or reduced-reference (RR), and no-reference (NR). Reduced reference image quality assessment (RR IQA) gives a realistic solution for automatic image quality estimation in different kinds of applications where only partial information of the original or reference image is available. The idea of RR IQA's to use less information about the image and obtain higher evaluation precision. |
| Starting Page | 1635 |
| Ending Page | 1639 |
| File Size | 604214 |
| Page Count | 5 |
| File Format | |
| e-ISBN | 9781479980819 |
| DOI | 10.1109/ICCSP.2015.7322795 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-04-02 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Visualization Histograms Accuracy Quantization (signal) Structural Similarity Information fidelity Receivers Singular value decomposition (SVD) Image quality assessment (IQA) Vector Quantization Distortion measurement Indexes |
| Content Type | Text |
| Resource Type | Article |
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