A Comprehensive Framework for Image Inpainting

Abstract

Inpainting is the art of modifying an image in a form that is not detectable by an ordinary observer. There are numerous and very different approaches to tackle the inpainting problem, though as explained in this paper, the most successful algorithms are based upon one or two of the following three basic techniques: copy-and-paste texture synthesis, geometric partial differential equations (PDEs), and coherence among neighboring pixels. We combine these three building blocks in a variational model, and provide a working algorithm for image inpainting trying to approximate the minimum of the proposed energy functional. Our experiments show that the combination of all three terms of the proposed energy works better than taking each term separately, and the results obtained are within the state-of-the-art.

An improved method for color image editing

“…The proposed method is compared with the previous approaches suggested in [1,[5][6][7][8]12,15,[18][19][20][21] by utilizing seamless and mixed seamless image cloning, arrangement of local lightness variation, texture flatting, multiresolution cloning considering the color fidelity, covariant inpainting, image completion, curvature-preserving PDE-based inpainting, combined PDE and texture synthesis, and variational inpainting approaches. The methods are tested on color images containing RGB color space and some images in referenced papers were utilized in these performed tests.…”

“…In recent years, many notable approaches have been developed for image inpainting, or completion [14,15,[17][18][19][20][21][22]. Our proposed method employs trace-based PDE method in which the local geometry of the color image can be calculated based on all the information contained in each of the color channels as follows:…”

“…Figure 21 shows the result of constrained PDE-based algorithm in [15], variational inpainting method in [21], and our covariant inpainting approach. Unlike other methods, our method gives a good result; however, two different patches must be selected by the user because of not being able to remove the object from the image efficiently.…”

Challenges of close-range underwater optical mapping

“…The framework is based on the partial differential equation with Dirichlet boundary conditions which specifies the Laplacian of an unknown function over the domain of interest, along with the unknown function values over the boundary of the domain. As an extension of the technique presented in [17], Pérez et al proposed to modify the problem of image interpolation through Poisson equation by introducing further constraints in the form of a guidance field. In the same context, Levin et al [5] proposed a method based in several cost functions for the evaluation of the quality of the stitching defined on the gradient domain.…”

Evolução de filtros ótimos com algoritmo fireworks para análise por níveis de erro em imagens comprimidas com perdas

“…As técnicas para a construção destas falsificações são diversas. Em [1] algumas destas são citadas, como cortar e colar, conhecida como clonagem [2], matting para ambientar mudanças [3], cortes em grafos para descoberta de limitesótimos de composição [4], síntese de texturas [4] e abordagens variadas para síntese de conteúdo [5,6].…”