Color separation and screen hanging technology of

2022-09-23
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Color separation and hanging technology of color images (Part 2)

3 a hanging method of color images

3.1 hanging basics

after color separation, the image is four gray-scale images with continuous tones. In 4-color printing, only one ink can be used each time, and the ink concentration remains unchanged. In order to obtain continuous tone during printing, it is necessary to hang the gray image. Hanging, also known as adding, is the process of decomposing a continuous tone image into dots. The added image uses the size and density of points to reflect the depth of the actual color of the image. Based on human visual effects, when observing the image from a close distance, the point and its surrounding space create a continuous tone illusion, the larger point looks dark, and the smaller point looks bright; Areas with dense dots look dark, and areas with sparse dots look bright. There are many methods of hanging, which can be divided into front-end hanging and back-end hanging according to the different graphics and positions; According to the different forming point methods, it can be divided into amplitude modulation (AM) and frequency modulation (FM) hanging methods. Front end hanging is also called software hanging. It is to hang the image before arranging and outputting, and then store the image data after hanging on the disk for calling when printing and outputting. The characteristics of this hanging method are: slow processing speed, large disk space, but strong flexibility, easy to upgrade and change. Back end hanging is also called hardware hanging. It is a high-speed hanging method for images by grid processor rip while arranging and outputting images. The characteristics of this method are: fast processing speed, save disk space, but need rip support, not easy to upgrade, poor flexibility. Amplitude modulation hanging is a method to realize halftone printing by changing the size of printing points during printing. The color of large points is dark, and the color of small points is bright. In this method, moire will be produced due to the interference of grid pattern. This is a traditional hanging technology. FM hanging is a method for Anqing to build a first-class industrial base of new chemical materials to print dots of the same size in random patterns, and to realize halftone by changing the sparsity of dots. The growth of China's plastic machinery industry has ushered in the golden period of Kemen growth and rapid growth. Where there are many dots, the color is dark, and where there are few dots, the color is bright. In this method, the points are placed irregularly, and the printed matter will not form certain lines and interference patterns

3.2 error dispersion method

error dispersion method is a front-end FM hook method, which is based on error method. The error method compares the gray value of each image point of the original image with the threshold value. The image points larger than the threshold value are recorded as white points, and the image points smaller than the threshold value are recorded as black points. Using this method, the gray-scale image with continuous tone can be halftoned, so the black-and-white contrast of the image is too obvious, and the effect is not good. The error dispersion method produces halftone points by comparing the gray value of the image point with the threshold value, and spreads the error between the gray value of the image point and the threshold value to the image points around the image point, so that the halftonization error of the point is not obvious in the final result. For example, for an image with 256 gray levels, the threshold is 256/2=127, and the gray level of an image point is 150. After comparison, it is known that the point should be recorded as white, but in fact, the point is not really white, and the gray difference between the point and white is 23. Spread the error of 23 to the image points around the point in a certain way, so that the error does not have a significant impact on the output result. There are many methods to disperse the error to the surrounding points. The following describes several commonly used error dispersion algorithms:

· Floyd Steinberg filtering algorithm x7351, where X represents the gray value of a point in the image. The algorithm first compares the gray value of X image point with the threshold value. The image point is marked as 1 or 0, that is, white or black. Then it calculates the error, assigns the error to the surrounding points, and modifies the gray value of the surrounding points. In this filtering algorithm, 7/16 of the error is added to the first image point on the right of X, 3/16 of the error is added to the first point on the left of the next line, 5/16 of the error is added to the image point on the right of the next line, and 1/16 of the error is added to the first point on the right of the next line. In this way, the error of X image point is dispersed to the surrounding image points. This process is repeated, and each image point in the image is subjected to such halftonization and gray value correction, and finally a halftone image reflecting the hierarchical relationship of the original image is obtained. This method, theoretically speaking, is already very good, and can well reflect the hierarchical relationship and color of the original image. However, the more points we disperse the error, the better the effect will be. Therefore, a filter that can involve many points is proposed

· Stucki filtering algorithm this algorithm further improves the Floyd algorithm. Because it involves more points, the output image effect is good, but it needs a lot of operations, so the speed of processing data is slow. X similarly, X is the gray value of the pixel point. After halftoning compared with the threshold, add 8/42 of the error to the gray value of the first image point on the left of X, 4/this has special significance. 42 is added to the gray value of the second image point on the left of X, 2/42 is added to the gray value of the second image point on the left of the next line, and so on, until 1/42 of the error is added to the gray value of the second image point on the right of the next line of X. Similarly, such halftoning and error correction processing can be carried out for each image in the image at the time of deformation or aging (cracks), and a better halftone output image can be obtained. The disadvantage of this filter is that it runs slowly and requires a lot of integer division and multiplication

· Burks filtering algorithm

this algorithm is a compromise between the running speed and the amount of data of the above two algorithms, involving many image points, and only simple shift, addition and subtraction operations. It adopts the following error distribution method: similarly, X is the gray value of image points. After halftoning compared with the threshold, several times of 32% of the error is added to the corresponding image points around x, one by one to each image point in the image

for any of the above algorithms, when the error is dispersed, if each image point is always processed one scan line from left to right, the error of one scan line will be simply added to the next line, resulting in the accumulation of errors, which is shown in the output graph that the image has a driving trend. Therefore, when scanning, the's' shape scanning method is often used, that is, odd rows are scanned from left to right, even rows are scanned from right to left, and so on until the last row. In the interface software we designed, the above three algorithms are provided at the same time. Users can choose one of them according to the requirements of image printing quality and processing speed

4 Conclusion

the color image color separation method and hanging method used in this paper have been successfully used in the color electronic map publishing system of a graphics research institute, and this method can be extended to other color electronic publishing systems

Author: zhanghuijuan, zhaihongming, microcomputer development

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