Today, digital inpainting technology is being widely used. The trend is to achieve automatic detection and remove scratches and smudges in pictures or movies. For some image processing software, such processing can be completed, but it is usually a complicated manual process.
The basic idea of â€‹â€‹the image inpainting algorithm is to smoothly spread diffusion information forward along the same color line around the trimmed area. The user only needs to point out the area to be retouched, and the remaining work can be automatically completed within a few minutes according to the algorithm. The image that was painted is very clear and there is no visible human color addition. This result can be used as a final repair result or to provide an initial direction for manual repair. Therefore, the total repair time is reduced from the workload.
In the literature related to digital inpainting technology, we find that there are mainly three types of related work. The first category involves the restoration of films (video sequences), the second category is related to the work of texture synthesis, and the third type of work is a topic that is rarely studied, namely disocclu sion (removing obstacles), although the prospects are very broad.
First of all, one area that is related to digital inpainting is also a very active area for the recovery of damaged videos (video sequences). The main idea used here is to repair damaged video frames by using past or future continuous frame information. Of course, this general method cannot be used to handle static images or still scenes.
Another area is texture synthesis. The basic idea of â€‹â€‹this technique is to first select a texture and then composite it into the areas that need to be filled (such as holes). This is a very simple technique that can produce incredible results. Although a number of well-known texture synthesis techniques have been reported in a large number of documents, these algorithms must allow the user to select areas or holes to fill the texture. For images that are to be retouched, they may have a variety of different structures. The user then needs to work on a large number of divisions of the image and then find the corresponding replacement area. Although some of the search work can be done automatically, it is very time-consuming and it also takes a lot of parameters. In addition, some texture synthesis algorithms can also be used to recreate a preselected texture that fills in the area to be painted.
The last type of work is the work on dis occlusion and line continuation. This type of work is also heavily reported in some literature, but it is all basic work, and everyone has not done it yet. Study in depth. In the algorithm for performing disocion (remove obstacles), the purpose of image segmentation is mainly to remove the occlusion. The basic idea is to connect the r-type with a flexible minimum-estimated curve at the same gray level. contact.
Masnou and Morel recently proposed a general variational formula for disocclusion processing and a very valuable algorithm to implement some ideas using this formula based on extending these ideas. This algorithm implements the retouching process by connecting the points of equal illumination line of the boundary area to be filled with short-range curves.
Researchers are now developing a large number of computer technologies for automatic image reconstruction. In such an actual application, the user simply selects the area to be restored and the computer automatically completes the remaining work. Such computer technology can significantly reduce the time and effort of digital image processing. It can not only fill in the blank areas, but also remove some unrelated objects, remove the text placed on the images, and transfer the audience in certain backgrounds. , or the political enemy of a particular character in a given scene. Such processing can also increase the resolution of the image and correct the lost information of the digital image during transmission. Of course, the results obtained will not always be satisfactory, but it will greatly reduce the overall repair time.
In addition, the publication strives to display clear images on the page with high resolution. Software that increases the resolution of pictures has been widely used, and digital inpainting technology is also a possible solution.
Of course, inpainting techniques are just as much as possible to make up for missing images, whether they are digital or manual. In most cases, there are many solutions for how to fill a crack and produce a plausible result. The final judgment of right and wrong depends on the eyes of bystanders.
Nowadays, no matter who, as long as you use software, you can easily modify digital images. You can remove the red-eye effects of a flash camera. You can also transfer people from a crowded room to a secluded beach. It is more than sufficient to use this technique to â€œdeceiveâ€ ordinary peopleâ€™s eyes.
In the field of video restoration, automatic image retouching technology has played an important role. By converting the continuous frames of the movie into digital image sequences, we can process it. For a frame of image to be repaired, it can be compared with the adjacent frames, and useful information can be extracted from the adjacent frames to achieve the scratches and stains in the repaired movie.
Static digital retouching techniques are relatively more difficult and subjective. Because there is no available information from neighboring frames or other sources. Then, the restorer can only rely on any visible detail around the blank area.
In short, the image inpainting technology has attracted more and more attention, and its application is very extensive. Whether it is in the printing industry, the film and television industry or the advertising industry, it can greatly reduce costs, reduce workload, and increase efficiency. Therefore, it is an area that cannot be ignored. At present, the domestic research in this area is almost a blank, and foreign countries have already started this work, but it is also in its infancy. Therefore, the potential of developing image inpainting technology is very large.
Source: "Printing World"
Author: Liying Yuan Zhoushi Sheng College of Printing and Packaging Engineering, Xi'an University of Technology
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