Feature similarity-based non-local neighborhood gray level image colorization method

A technology of neighborhood grayscale and similarity, applied in image data processing, graphics and image conversion, instruments, etc., can solve the problems of not considering image texture information, color mixing, not taking into account, etc.

Active Publication Date: 2015-08-19
WENZHOU UNIVERSITY
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Problems solved by technology

This method has two main disadvantages: on the one hand, because the method is based on a local colorization algorithm, the colorization results of each area are still relatively dependent on user input, and color bleeding is prone to occur
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  • Feature similarity-based non-local neighborhood gray level image colorization method
  • Feature similarity-based non-local neighborhood gray level image colorization method
  • Feature similarity-based non-local neighborhood gray level image colorization method

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Embodiment Construction

[0119] The present invention will be further described by the following examples in conjunction with the schematic flow chart.

[0120] The present invention will be described in detail below in conjunction with the accompanying drawings: the non-local neighborhood grayscale image colorization method based on feature similarity; this embodiment is implemented on the premise of the technical solution of the present invention, and combines detailed implementation methods and process, but the protection scope of the present invention is not limited to the following examples.

[0121] like figure 1 As shown, the non-local neighborhood grayscale image colorization method based on feature similarity described in this embodiment includes the following nine steps:

[0122] (1) Input a grayscale image in the RGB color space to be processed as the input image sI, whose width and height are recorded as width and height;

[0123] (2) Use the structure tensor to obtain the local salient ...

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Abstract

The invention provides a feature similarity-based non-local neighborhood gray level image colorization method. A gray level image is given by a user as an input image; a marked feature direction field is obtained through the input image; a textural feature vector field is obtained according to the marked feature direction field and the input image; a structure chart is obtained by calculating the input image with a relative total variation method; a high-dimensionality feature vector field is constructed through the structure chart, the textural feature vector field, the gray level image and an image space coordinate system; the nearest neighbor of each pixel is obtained through the feature vector field; the user performs little artificial coloring on the input image to obtain a colored image, and converts the input image and the colored image to a Lab color space; in combination of the colored image and the nearest neighbor of each pixel, a sparse linear equation set is constructed, and the sparse linear equation set is solved to obtain a target image; and the target image is converted to an RGB color space to obtained a colorized image. The method takes brightness, coordinates and textual features into account, and improves a colorization effect.

Description

technical field [0001] The invention relates to a grayscale image colorization method, in particular to a non-local neighborhood grayscale image colorization method based on feature similarity. Background technique [0002] Colorization is a computer-aided process that adds color to a black and white image or video. This technology is currently widely used in the fields of film and television, medical treatment, space exploration, industry, and science. Generally, colorization methods are divided into two categories: colorization methods based on reference pictures and colorization methods based on user graffiti interaction. The colorization method based on the reference picture is the process of transferring the color in the reference picture to the target image according to a certain degree of correlation. Although this type of method can obtain better colorization results, it relies heavily on reference pictures, thus restricting the development of this method. However...

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Application Information

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IPC IPC(8): G06T3/00
Inventor 赵汉理聂桂芝厉旭杰
Owner WENZHOU UNIVERSITY
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