A non-parametric blur measure based on edge analysis for image processing applications

A nonparametric image blur measure is presented. The measure is based on edge analysis and is suitable for various image processing applications. The proposed measure for any edge point is obtained by combining the standard deviation of the edge gradient magnitude profile and the value of the edge gradient magnitude using a weighted average. The standard deviation describes the width of the edge, and its edge gradient magnitude is also included to make the blur measure more reliable. Moreover, the value of the weight is related to image contrast and can be calculated directly from the image. Experiments on natural scenes indicate that the proposed technique can effectively describe the blurriness of images in image processing applications.

1. Introduction

A measure of the sharpness or blurriness of edges in an ‘image can be useful for a number, of applications in image processing, such as checking the focus of a camera lens,.helping to identify shadows (whose edges are often less sharp than object edges), the separation of variations in illumination from the reflectance of the objects in an image’ (known as. intrinsic image extraction), and in-focus areas (or foreground) ‘VS. out-of-focus (or background) in an image.