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Understanding low resolution facial image from image formation model

Wang, H (2018) Understanding low resolution facial image from image formation model.

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Abstract:A camera contains a planar,rectangle photosensitive sensor divided into square pixels and the RGB color is interpolated in the pixel when light reflect off the object traverse the camera lens and hit the sensor. All today’s digital images have gone through some kind of degradations and restorations during acquisition,coding,transmission and processing steps. This degradation and restoration disturb the original information of image from different level. Normally, high resolution image represents the original image better than the low resolution ones since it contains more discriminative information. Down sampling high resolution image gives the image are far more better quality than the real low resolution ones since many processes are playing a role in image formation procedure. For instance, the viewing angle is much smaller when the image recorded at a large distance, resulting geometric difference between the image captured closeby. In this paper, a camera model is developed to study and analyze the image formation procedure. Based on the model, all the parameters are carefully estimated by computing the minimal average difference in either spatial domain or frequency domain. The experimental results showed that the proposed method provide a valid but simple solution to narrow down the difference between different resolution facial images visually and numerically.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Electrical Engineering BSc (56953)
Link to this item:https://purl.utwente.nl/essays/75273
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