کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6952126 | 1451750 | 2014 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
No reference image quality classification for JPEG-distorted images
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
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چکیده انگلیسی
In this paper, we address the Image Quality Assessment (IQA) of JPEG-distorted images. We approach the IQA field by focusing on a classification problem that maps different objective metrics into different categorical quality classes. To this end, we adopt a machine learning classification approach, where No Reference (NR) metrics are considered as features, while the assigned classes come from psycho-visual experiments. Eleven NR metrics have been considered: seven specific for blockiness and four general purpose. We evaluate the performance of single metrics and investigate if a pool of metrics can reach better performances than each of the single ones. Five as well as three quality classes are considered, and the corresponding classifiers are tested on two well known databases available in the literature (LIVE and MICT), and on a new database (IVL) presented in this paper.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Digital Signal Processing - Volume 30, July 2014, Pages 86-100
Journal: Digital Signal Processing - Volume 30, July 2014, Pages 86-100
نویسندگان
Silvia Corchs, Francesca Gasparini, Raimondo Schettini,