کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
537181 870770 2015 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Motion silencing of flicker distortions on naturalistic videos
ترجمه فارسی عنوان
خاموش شدن حرکت از تحریف سوسو زدن در فیلم های طبیعت گرایانه
کلمات کلیدی
خاموش شدن حرکت ماسک تصویری تحریف سوسو زدن، قابل مشاهده بودن اعوجاج، کیفیت تصویر
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی


• We study motion silencing of flicker distortions on naturalistic videos.
• Flicker visibility is strongly reduced when the speed of object motion is large.
• Motion silencing of flicker distortions is pronounced when video quality is poor.
• We propose a model of flicker visibility on naturalistic videos.
• The model prediction of flicker visibility correlates well with human perception.

We study the influence of motion on the visibility of flicker distortions in naturalistic videos. A series of human subjective studies were executed to understand how motion silences the visibility of flicker distortions as a function of object motion, flicker frequency, and video quality. We found that flicker visibility is strongly reduced when the speed of coherent motion is large, and the effect is pronounced when video quality is poor. Based on this finding, we propose a model of flicker visibility on naturalistic videos. The target-related activation levels in the excitatory layer of neurons were estimated for a displayed video using a spatiotemporal backward masking model, and then the flicker visibility is predicted based on a learned model of neural flicker adaptation processes. Experimental results show that the prediction of flicker visibility using the proposed model correlates well with human perception of flicker distortions. We believe that sufficiently fast and coherent motion silences the perception of flicker distortions on naturalistic videos in agreement with a recently observed “motion silencing” effect on synthetic stimuli. We envision that the proposed model could be applied to develop perceptual video quality assessment algorithms that can predict “silenced” temporal distortions and account for them when computing quality judgments.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing: Image Communication - Volume 39, Part B, November 2015, Pages 328–341
نویسندگان
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