Image Colorization is the problem of defining colors for grayscale images. Recently many research works have been conducted to propose fully-automatic colorization methods. However, these papers failed in colorizing images with multiple objects accurately. This might be because dealing whole multi-object image as a single input. Following efforts made last few years, this paper aims at studying...

Region-based approaches have been proposed to computerassisted colorization problem, typically using shape similarity and topology relations between regions. Given a colored frame, the objective is to automatically colorize consecutive frames, minimizing the user effort to colorize the remaining regions. We propose a new colorization algorithm based on graph matching, using Belief Propagation t...

This paper presents a novel approach to grayscale image matting and colorization. The first part of this approach is an efficient grayscale image matting algorithm in Bayesian framework. The foreground and background color distributions, and the alpha’s distribution are modelled with spatially varying sets of Gaussians. The major novelties of this matting algorithm are the introduction of alpha...

In this paper a novel method for machine-based black and white films colorization is presented. The kernel of the proposed scheme is a trained artificial neural network which maps the frame pixels from a grayscale space into a color space. We employ the texture coding method to capture the line/texture characteristics of each pixel as its most significant gray scale space feature, and using tha...

We propose in this paper an automated colorization of segmented images based on a color harmony rule defined by Itten called the contrast of proportion. Artists create an image drawing a sketch and filling its regions following harmony rules. The most significant regions are generally filled first because of their meaning. Then the other regions are filled depending on the previous colors. Our ...

This paper targets two related color manipulation problems: Color transfer for modifying an image colors and colorization for adding colors to a greyscale image. Automatic methods for these two applications propose to modify the input image using a reference that contains the desired colors. Previous approaches usually do not target both applications and su er from two main limitations: possibl...

Automatic image colorization consists in adding colors to a new greyscale image without any user intervention. The problem, stated like this, is ill-posed, in the sense that one cannot guess the colors to assign to a greyscale image without any prior knowledge. Indeed, many objects can have different colors: not

By embedding images as surfaces in a high dimensional coordinate space defined by each pixel’s Cartesian coordinates and color values, we directly define and employ cotangent-based, discrete differentialgeometry operators. These operators define discrete energies useful for image segmentation and colorization.