Image sharpness evaluation method based on normal gradient feature

An evaluation method based on the normal gradient feature of image texture is proposed to describe the imaging sharpness of stereo objects. The method can be summarized by four steps. Firstly, median filter is utilized to remove noise and threshold segmentation is applied to binary the image. The second step is edge detection which is realized by Canny algorithm. In the following procedure, the gray value in a fixed range along the normal direction of the edge is extracted for least square method curve fitting. Lastly, the average index coefficient D value is taken as the sharpness evaluation index for the image. In this paper, the sharpness evaluation method based on the normal gradient feature of image texture is dedicated to the local region of interest evaluation in different planes, so as to achieve the accurate evaluation of the sharpness requirements for specific needs, such as high-definition required object recognition. Experiments show that the proposed method can accurately evaluate the image definition. The method also has the advantages of single peak, high sensitivity and strong stability, which may shade lights in local definition evaluation and high-accuracy object recognition.