Research On Sharpness Evaluation Of Real Camera Images

Image quality evaluation has a key role in modern science and technology,especially in visual signal processing such as image restoration,image fusion,and biomedical imaging.The quality of the image directly affects the visual perception and user experience.On regards to the speedy advancement in recent multimedia technology,acquiring accurate and reliable image quality evaluation method becomes very important and has extensive applications in image development.An objective of image quality evaluation is to obtain consistent quality scores that are subjective to the human being's judgment.Designing a new computational model to mimic human beings in predicting image quality.This paper studies the image quality evaluation from the perceptual characteristics of images.In particular,this thesis offers an improved algorithm for real camera images sharpness evaluation.Firstly,the existing image sharpness evaluation methods are studied.On the basis of the characteristics of the image free energy and the contrast,an improved noreference image sharpness evaluation algorithm is proposed.The experimental results on the real camera image quality databases demonstrates an improved performance algorithm with better subjective rating consistency than the relevant popular metrics.