1. Field of the Invention
The preset invention relates to an image processing method and apparatus, and particularly to formation of un-sharp signals equivalent to a blurred image, and also to image processing using such un-sharp signals.
2. Description of the Related Art
Un-sharp masking processing is well-known as a means for emphasizing images, and is often employed in the art of photography, and further has recently come to be used as means for emphasis processing of digital images in medical X-ray systems ("Newest Movements in Image Processing Algorithms"; Edited by Takagi, Toriwaki, and Tamura; Shin-Gijutsu Communications).
Now, with the input image as f(x, y), the resultant image g (x, y) obtained by un-sharp masking processing can be expressed as follows in Expression (1): EQU g(x, y)=f(x, y)+c.times.{f(x, y)-f.sub.av (x, y)} (1)
Now, f.sub.av (x, y) represents the local average value for point (x, y), and is obtained from the n.times.m pixel area surrounding the point (x, y), and generally can be calculated using a simple average pixel value as shown in the following Expression (2): ##EQU1##
This local average value f.sub.av (x, y) represents the blurred image formed by blurring the input image f(x, y), and the greater the surrounding pixel area of which the local average is obtained, the more blurred the image becomes. Further, the second term in Expression (1) includes high-frequency components of the input image due to difference, the un-sharp masking process being to add high-frequency components multiplied by coefficient c to the input image.
Also, a photography method using an analog filter is known in medical X-ray radiography, for allowing for better observation of the mediastinum in simple chest photography and chest tomography, which can be realized by processing the image captured with normal radiography, even without using analog filters. ("Development of self-compensating digital filters with CR"; Ohtani et al; Japan Radiation Technology Association Magazine, Volume 45, Issue 8, p.1030, 1989)
The resultant image g'(x, y) from processing by this self-compensating digital filtering process can be expressed by the following Expression (3): EQU g'(x, y)=f(x, y)+F{f.sub.av (x, y)} (3)
wherein (x, y) represents the input image, and also wherein f.sub.av (x, y) represents the local average value for point (x, y) and indicates the blurred image of which the input image f(x, y) has been blurred, as with Expression (1). Also, F{*} is a function representing an analog filter. PA1 so that the amount of calculation for calculating the local average value for a certain point (x, y) is multiplied by k.sup.2.
However, with the above-described un-sharp masking processing and self-compensating digital filtering process in the known example, both are image processing using a blurred image represented by f.sub.av (x, y), so the amount of calculations for creating the blurred image has been the predominant factor in the processing time thereof.
Also, there is a problem in the creation of the blurred image, in that enlarging the n.times.m pixel area for calculating the local average value to obtain an image with a greater amount of blurring substantially decreases processing speed. For example, in the event that the n.times.m pixel area for calculating the local average value is multiplied by k (an integral wherein k&gt;0), the area for calculating the local average value becomes: EQU Kn.times.Km=K.sup.2.times.(n.times.m)