An Algorithm For Image Sharpness Estimation Based On DTCWT

Image sharpness estimation is an important part of digital image processing,and it plays an important role in the field of image feature extraction,image quality assessment and image restoration.At present,there are two ways of image sharpness estimation: subjective estimation and objective estimation.Subjective estimation method uses visual as a criterion,result is based on the observer's estimation on the clarity of the image;objective estimation method is to express the subjective feelings of the people of the image using the mathematical model of quantitative analysis.The subjective evaluation method requires special training to the image interpretation personnel,the evaluation process is time-consuming,and the economical efficiency is unsatisfied.Objective estimation method is based on mathematic theory,which is fast and stable,also can provide quantitative data,but it ignores the human visual characteristics,sometimes objective estimation does not consistent with people's subjective feeling.So it is very important to develop an objective quality assessment method which is consistent with the subjective perception of the image.The Algorithm proposed in this paper use the dual tree complex wavelet transform coefficients which can more accurately represent the characteristics of the image.This Algorithm combined with FISH and FISH_bb algorithm,proposed a multi-scale and multi-direction image sharpness estimation.In this Algorithm first we decompose the input image using a three layer dual-tree complex wavelet transform,then calculate energy logarithm by using the discrete wavelet sub-band coefficients,finally,calculate a weighted sum of these logarithmic energy to obtain a value of the image sharpness.Experiments show that,compared with FISH and FISH_bb algorithm,the algorithm proposed in this paper can ensures the speed of calculation,in the meantime improves the accuracy of the image sharpness estimation.