1. Field of the Invention
The present invention relates to an image processing method, an image processor and a storage medium to perform half tone processing on input images using an error diffusion method, and more particularly to an image processing method, an image processor and a storage medium thereof wherein the geometric texture and graininess of output images are improved with the error diffusion method.
2. Description of the Related Art
Recently full color image processing has become possible with advances in color image processing technology. For example, processing with 256 grayscale levels is performed for each one of cyan C, magenta M and yellow Y. However, such a device as a display and a printer, to display and print these colors, cannot display or print full color images since the number of grayscale levels is limited. Therefore, such a device as a display and a printer, where the number of grayscale levels which can be reproduced is limited, converts a full color input image to a half tone image by the error diffusion method.
The error diffusion method uses an algorithm to obtain half tone images where grayscale is satisfactorily preserved by diffusing the quantization errors, which are generated when input images are quantized by the number of grayscale levels possible in the output device, into the peripheral pixels.
However, a shortcoming of the error diffusion method is the generation of geometric texture, such as the texture generated in the low density dot area (area where the density of block dots is low) of the output image (this texture is called “worm”), and the texture generated in the high density dot area (area where the density of black dots is high) (this texture is called “fingerprint”), and many improvements have been attempted in the prior art. The improvement techniques which have been proposed will be described below.
The first method is a two-way scan (Ulichney, 1987) which scans an input image in two ways, where worm is decreased since the diffusion direction of the quantization errors is dispersed in the low dot density area.
The second method is an error filter switching system, which switches the error filters to diffuse the quantization errors into the peripheral pixels (R. Eschbach, “Reduction of artifacts in error diffusion by means of input dependent areas”, Journal of Electronic Imaging, 2 (4), pp. 352-358, (1993)). Depending on the input pixels and the peripheral pixels thereof, several types of error filters are used to decrease worm and fingerprint. Worm decreases as the filter to be used becomes larger in size.
A system combining the two-way scan system and the error filter switching system has also been proposed (e.g. Japanese Patent Laid-Open Application No. 9-65126).
The third method is a sine wave superimposing system (Y. Kishimoto, M. Nose, R. Saito and H. Kotera, “Improved error diffusion method with AM/FM periodic noise”, Rroc. IS&T sNIP15, pp. 366-369 (1999)), where dots are corrected and arranged by superimposing a sine wave for modulating the amplitude and the frequency on the input pixel values before quantization processing. The volume of calculation is relatively low.
The above mentioned prior art, however, has the following problems.
In the first method, two-way scanning, worm is decreased since the diffusion direction of quantization errors is dispersed in the low dot density area, but fingerprint is amplified by the interference of quantization errors in the high dot density area.
In the second method, which is a combination of the error filter switching system and the two-way scan, geometric texture (worm and fingerprint) decreases but uniform cyclic dot patterns, such as half tone dots, cannot be created in the low dot density area, the graininess of dots becomes salient, and the color reproduction range does not improve.
In the third method, the sine wave superimposing system, sine waves are applied simply according to the intensity of the input level, so the edges of the output image become unclear, and images where density varies greatly cannot be improved very much.
With the above mentioned techniques alone, it is difficult to improve both worm and fingerprint simultaneously, and the indiscriminate combination of techniques merely increases the volume of calculation.
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