Vorticity Transport Equation-Based Shadow Removal Approach for Image Inpainting

IF 2 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Xiaoying Ti, Li Yu, Quanhua Zhao
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引用次数: 0

Abstract

Shadows are common in many types of images, causing information loss or disturbance. Shadow removal can help improve the quality of the digital image. If there is no effective information available to restore the original image in the shaded area, the interpolation-based inpainting technique can be used to remove the shadow from the digital image. This image inpainting technique typically involves establishing and solving partial differential equations (PDEs), an iterative solving process that is very time-consuming. To solve the time-consuming problem, a method that introduces the fast marching method (FMM) into the vorticity transport equation (VTE) is demonstrated. VTE is a type of partial differential equation describing two-dimensional fluids. FMM is a numerical scheme for tracking the evolution of monotonically advancing interfaces via finite difference solution of the eikonal equation. The proposed method contains three main steps: (a) by investigating the relationship between VTE and the traditional PDE-based image inpainting method, a new image inpainting model using VTE is developed;(b) the area to be inpainted is divided into boundaries that shrink in layers from the outside inwards using FMM; and (c) the VTE image inpainting model is converted into a weighted average form to coordinate with FMM. The visual and quantitative evaluation of the experimental results of shadow removal shows that the proposed method outperforms PDE-based and state-of-the-art methods in terms of shadow-removal effect and running time. The results also show that our method excels at inpainting images with near-smooth textures and simple geometric structures and where the pixels to be inpainted are continuous with neighbouring pixels.

基于涡量输运方程的图像去影方法
阴影在许多类型的图像中都很常见,会导致信息丢失或干扰。去除阴影有助于提高数字图像的质量。如果在阴影区域没有有效的信息来恢复原始图像,则可以使用基于插值的补图技术来去除数字图像中的阴影。这种图像绘制技术通常涉及建立和求解偏微分方程(PDEs),这是一个非常耗时的迭代求解过程。为了解决求解速度慢的问题,提出了在涡量输运方程(VTE)中引入快速推进法的方法。VTE是一类描述二维流体的偏微分方程。FMM是一种通过对角方程的有限差分解来跟踪单调推进界面演化的数值格式。该方法包括三个主要步骤:(a)通过研究VTE与传统的基于pde的图像补绘方法之间的关系,开发了一种新的基于VTE的图像补绘模型;(b)使用FMM将待补绘区域划分为由外向内逐层收缩的边界;(c)将绘制模型中的VTE图像转换为加权平均形式,与FMM进行协调。对阴影去除实验结果的可视化和定量评价表明,该方法在去除阴影效果和运行时间方面优于基于pde的方法和目前最先进的方法。结果还表明,该方法在纹理接近光滑、几何结构简单且待绘制像素与相邻像素连续的图像中表现优异。
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来源期刊
IET Image Processing
IET Image Processing 工程技术-工程:电子与电气
CiteScore
5.40
自引率
8.70%
发文量
282
审稿时长
6 months
期刊介绍: The IET Image Processing journal encompasses research areas related to the generation, processing and communication of visual information. The focus of the journal is the coverage of the latest research results in image and video processing, including image generation and display, enhancement and restoration, segmentation, colour and texture analysis, coding and communication, implementations and architectures as well as innovative applications. Principal topics include: Generation and Display - Imaging sensors and acquisition systems, illumination, sampling and scanning, quantization, colour reproduction, image rendering, display and printing systems, evaluation of image quality. Processing and Analysis - Image enhancement, restoration, segmentation, registration, multispectral, colour and texture processing, multiresolution processing and wavelets, morphological operations, stereoscopic and 3-D processing, motion detection and estimation, video and image sequence processing. Implementations and Architectures - Image and video processing hardware and software, design and construction, architectures and software, neural, adaptive, and fuzzy processing. Coding and Transmission - Image and video compression and coding, compression standards, noise modelling, visual information networks, streamed video. Retrieval and Multimedia - Storage of images and video, database design, image retrieval, video annotation and editing, mixed media incorporating visual information, multimedia systems and applications, image and video watermarking, steganography. Applications - Innovative application of image and video processing technologies to any field, including life sciences, earth sciences, astronomy, document processing and security. Current Special Issue Call for Papers: Evolutionary Computation for Image Processing - https://digital-library.theiet.org/files/IET_IPR_CFP_EC.pdf AI-Powered 3D Vision - https://digital-library.theiet.org/files/IET_IPR_CFP_AIPV.pdf Multidisciplinary advancement of Imaging Technologies: From Medical Diagnostics and Genomics to Cognitive Machine Vision, and Artificial Intelligence - https://digital-library.theiet.org/files/IET_IPR_CFP_IST.pdf Deep Learning for 3D Reconstruction - https://digital-library.theiet.org/files/IET_IPR_CFP_DLR.pdf
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