Colorization of grayscale images and videos using a semiautomatic approach

Jacob, Vivek George; Gupta, Sumana

doi:10.1109/icip.2009.5413392

Cited by 22 publications

(8 citation statements)

References 12 publications

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“…This method represents the concept of seed pixels propagation. In [2] the image pixels are divided into unique regions using the watershed segmentation [11]. The initial oversegmantation is removed by region flooding, so that the pixels are being merged as long as the number of segments is equal to the number of colour scribbles indicated by a user.…”

Section: State-of-the-art Colourisation Methodsmentioning

confidence: 99%

Fast image colourisation using the isolines concept

Smołka

2016

Multimed Tools Appl

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Colourisation is the process of adding colour information to monochromatic images and video sequences. Generally, colourised images are visually more attractive and they are advantageous in areas such as medicine, astronomy, microscopy or education, in which the visualisation of image information plays a crucial role. In this paper, we introduce a novel concept of grayscale image colourisation, which is based on the idea of isolines. The algorithm is straightforward, easy to implement, computationally efficient and it allows a very high colourisation quality to be obtained. The proposed approach utilises the distance transform applied to a grayscale digital image. The final colourisation is performed via the weighted blending of scribbled colours. The comparison with similar state-of-the-art colourisation techniques that is presented proves that the method is computationally more efficient while producing outputs that have the same high quality. Additionally, we provide the pseudocode for the easier implementation of the algorithm and show its multidisciplinary applications.

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Section: State-of-the-art Colourisation Methodsmentioning

confidence: 99%

Fast image colourisation using the isolines concept

Smołka

2016

Multimed Tools Appl

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“…In [10], a somewhat different design based on the image segmentation, is presented. The so-called "rainwater simulation technique" is a segmentation method of properly clustering the parts of the image into regions with the same colors.…”

Section: Literature Overviewmentioning

confidence: 99%

Overview of Grayscale Image Colorization Techniques

Smołka

2015

Color Image and Video Enhancement

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Colorization is the process of introducing color to grayscale digital images. In these images, each pixel has a scalar value representing its intensity. However, the pixels of color images contain more complex, three-dimensional information. Depending on a color model, the pixel attributes correspond to a three-value color representation. For the purpose of grayscale image colorization, we strongly advise the use of color representation, which allows easy luminance extraction. This makes the colorization simpler-we only need to estimate two chrominance channels, while the luminance of the colorized image remains unchanged.Despite plenty of color models, we cannot directly transform a one-dimensional grayscale value to a three-dimensional color space. We only get the luminance of the colorized image, while the two remaining color channels are still unknown. Therefore, the colorization may be performed in many different ways, achieving various outcomes. Additionally, it is difficult to objectively assess the final colorization results. We can compare the colorized version using standard image quality measures only if we have the color version of the image. The colorization of grayscale images without a reference has to be evaluated mainly subjectively.In general, there are two main types of colorization frameworks. The first one is the semiautomatic approach. In such a range of methods, a user has to indicate the color hints in form of scribbles within the grayscale image. The scribbles enable the algorithms deciding which colors have to be put in corresponding parts of the image. The colorization procedure in the semiautomatic approach may be visualized as color spilling over the image areas starting from the indicated scribbles.The automatic approach employs a color image that resembles the colorized grayscale picture. The algorithms rely on the similarities between the luminance B. Smolka ( ) · A. Popowicz

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“…For this problem, various algorithms have been proposed [1][2][3][4][5][6]. In [1][2][3], colorization algorithms are proposed using the segmentation technique. Because the performance of segmentation technique depends heavily on the property of each image, these algorithms can colorize only particular images.…”

Section: Introductionmentioning

confidence: 99%

Image colorization algorithm using series approximated sparse function

Uruma

Konishi

Takahashi

et al. 2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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This paper deals with an image colorization and proposes a new image colorization algorithm. Assuming that the difference of color values between neighbor pixels is given as a monotonically increasing function of the difference of grayscale values between neighbor pixels, a colorization function is proposed, and the colorization problem is formulated as the weighted least squares problem using this function. In order to reduce the dependence on the value of a parameter in the algorithm, this paper utilizes a finite series approximation and provides a fast colorization algorithm. Numerical examples show that the proposed algorithm colorizes a grayscale image efficiently.

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Colorization of grayscale images and videos using a semiautomatic approach

Cited by 22 publications

References 12 publications

Fast image colourisation using the isolines concept

Fast image colourisation using the isolines concept

Overview of Grayscale Image Colorization Techniques

Image colorization algorithm using series approximated sparse function

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