Research on Virtual Color Restoration of Complex Building System Based on Discrete Wavelet Transform

At present, image restoration has become a research hotspot in computer vision. The purpose of digital image restoration is to restore the lost information of the image or remove redundant objects without destroying the integrity and visual effects of the image. The operation of user interactive color migration is troublesome, resulting in low efficiency. And, when there are many kinds of colors, it is prone to errors. In response to these problems, this paper proposes automatic selection of sample color migration. Considering that the respective gray-scale histograms of the visual source image and the target image are approximately normal distributions, this paper takes the peak point as the mean value of the normal distribution to construct the objective function. We find all the required partitions according to the user’s needs and use the center points in these partitions as the initial clustering centers of the fuzzy C-means (FCM) algorithm to complete the automatic clustering of the two images. This paper selects representative pixels as sample blocks to realize automatic matching of sample blocks in the two images and complete the color migration of the entire image. We introduced the curvature into the energy functional of the p-harmonic model. According to whether there is noise in the image, a new wavelet domain image restoration model is proposed. According to the established model, the Euler–Lagrange equation is derived by the variational method, the corresponding diffusion equation is established, and the model is analyzed and numerically solved in detail to obtain the restored image. The results show that the combination of image sample texture synthesis and segmentation matching method used in this paper can effectively solve the problem of color unevenness. This not only saves the time for mural restoration but also improves the quality of murals, thereby achieving more realistic visual effects and connectivity.

Animation Design Based on 3D Visual Communication Technology

The depth synthesis of image texture is neglected in the current image visual communication technology, which leads to the poor visual effect. Therefore, the design method of film and TV animation based on 3D visual communication technology is proposed. Collect film and television animation videos through 3D visual communication content production, server processing, and client processing. Through stitching, projection mapping, and animation video image frame texture synthesis, 3D vision conveys animation video image projection. In order to ensure the continuous variation of scaling factors between adjacent triangles of animation and video images, the scaling factor field is constructed. Deep learning is used to extract the deep features and to reconstruct the multiframe animated and animated video images based on visual communication. Based on this, the frame feature of video image under gray projection is identified and extracted, and the animation design based on 3D visual communication technology is completed. Experimental results show that the proposed method can enhance the visual transmission of animation video images significantly and can achieve high-precision reconstruction of video images in a short time.

Realism in Data-Based Terrain Synthesis

<p>The landscapes on Earth are varied and complex, having been created by innumerous physical processes over millions of years. The creation of artificial terrain that replicates the realism of landscapes on Earth has been a major challenge for computer graphics. Many different approaches have been taken, including approximating the terrain with fractals and splines, simulating the terrain using models from the physical geography, and reconstructing terrain from elements of real-world data. A primary issue in the field of terrain synthesis is the lack of, and evaluation of, realism in synthesized terrain. This thesis identifies and discusses the flaws of existing data-based methods based on example-based texture synthesis methods. It provides improvements to an existing data-based method using algorithms from the field of geographic information science, and presents a novel algorithm, ``terrain-optimization'', based on the example-based texture synthesis technique of texture-optimization. Finally, it discusses a new approach to the experimental evaluation of terrain realism, with the largest experiment conducted to date. The results of this show that each of the tested methods is indistinguishable from reality in certain circumstances and that those circumstances differ for each method tested, and that subjects with a high level of expertise in physical geography are the most qualified for identifying real terrain from synthesized terrain. Overall, the thesis provides substantial analysis and evidence about the challenges of data-based terrain synthesis while also developing new approaches in the field that perform as well as existing state-of-the-art methods.</p>

Realism in Data-Based Terrain Synthesis

<p>The landscapes on Earth are varied and complex, having been created by innumerous physical processes over millions of years. The creation of artificial terrain that replicates the realism of landscapes on Earth has been a major challenge for computer graphics. Many different approaches have been taken, including approximating the terrain with fractals and splines, simulating the terrain using models from the physical geography, and reconstructing terrain from elements of real-world data. A primary issue in the field of terrain synthesis is the lack of, and evaluation of, realism in synthesized terrain. This thesis identifies and discusses the flaws of existing data-based methods based on example-based texture synthesis methods. It provides improvements to an existing data-based method using algorithms from the field of geographic information science, and presents a novel algorithm, ``terrain-optimization'', based on the example-based texture synthesis technique of texture-optimization. Finally, it discusses a new approach to the experimental evaluation of terrain realism, with the largest experiment conducted to date. The results of this show that each of the tested methods is indistinguishable from reality in certain circumstances and that those circumstances differ for each method tested, and that subjects with a high level of expertise in physical geography are the most qualified for identifying real terrain from synthesized terrain. Overall, the thesis provides substantial analysis and evidence about the challenges of data-based terrain synthesis while also developing new approaches in the field that perform as well as existing state-of-the-art methods.</p>

Co-occurrence based texture synthesis

As image generation techniques mature, there is a growing interest in explainable representations that are easy to understand and intuitive to manipulate. In this work, we turn to co-occurrence statistics, which have long been used for texture analysis, to learn a controllable texture synthesis model. We propose a fully convolutional generative adversarial network, conditioned locally on co-occurrence statistics, to generate arbitrarily large images while having local, interpretable control over texture appearance. To encourage fidelity to the input condition, we introduce a novel differentiable co-occurrence loss that is integrated seamlessly into our framework in an end-to-end fashion. We demonstrate that our solution offers a stable, intuitive, and interpretable latent representation for texture synthesis, which can be used to generate smooth texture morphs between different textures. We further show an interactive texture tool that allows a user to adjust local characteristics of the synthesized texture by directly using the co-occurrence values.

Calcium functional imaging with high-resolution CT in the inner ear

Although the otolith and otolith organs correlate with vertigo and instability, there is no method to investigate them without harmful procedures. We will create the technique for 3D microanatomical images of them, and investigate the in vivo internal state and metabolisms. The otolith and otolith organs images were reconstructed from a texture synthesis algorithm under the skull volume rendering algorithm using a cutting-plane method. The utricular macula was elongated pea-shaped. The saccular macula was almost bud-shaped. The changes in the amount of CaCO3 in the maculae and the endolymphatic sac showed various morphologies, reflecting the balance status of each subject. Both shapes and volumes were not always constant depending on time. In Meniere’s disease (MD), the saccular macula was larger and the utricular macula was smaller. In benign paroxysmal positional vertigo (BPPV), the otolith increased in the utricular macula but did not change much in the saccular macula. The saccule, utricle, and endolymphatic sac were not constantly shaped according to their conditions. These created 3D microanatomical images can allow detailed observations of changes in physiological and biological information. This imaging technique will contribute to our understanding of pathology and calcium metabolism in the in vivo vestibulum.