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Image retrieval based automatic grayscale image colorization

机译:基于图像检索的自动灰度图像颜色

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Colorization is an appealing area in the world of image processing. It has been used to increase the visual appeal of images such as old black and white photos, classic movies or scientific illustrations. Also, It has been very important in color image compression and video compression. Colorization, the task of coloring a grayscale image or video, involves assigning an intensity or luminance from the single dimension to a quantity that varies in three dimensions, such as red, green, and blue channels. Different colorization techniques are prevailing like hand coloring, semi automatic coloring and automatic coloring. Hand coloring and semi automatic coloring require intensive and perfect human interference. We are introducing a methodology for adding color to grayscale images in a way that is automatic and require little execution time. Towards this aim, a colorful image of the similar content as the grayscale image is taken, as an input source image by means of different image retrieval techniques. Then, the best matching source pixel is determined using luminance matching technique, for each pixel of the target grayscale image. Once a best matching source pixel is found, its chromaticity values are assigned to the target pixel while the original luminance value of the target pixel is retained.
机译:着色是在图像处理世界中的一种吸引人的区域。它已被用于增加旧黑白照片,经典电影或科学插图等图像的视觉吸引力。此外,它在彩色图像压缩和视频压缩方面非常重要。彩色,彩色图像或视频的任务涉及将从单个维度的强度或亮度分配到三维变化的量,例如红色,绿色和蓝色通道。不同的彩色技术是盛行的,如手着色,半自动着色和自动着色。手着色和半自动着色需要密集和完美的人性干扰。我们正在引入一种以自动的方式将颜色添加到灰度图像的方法,并且需要很少的执行时间。朝向此目的,通过不同的图像检索技术作为输入源图像作为输入源图像的类似内容的彩色图像。然后,对于目标灰度图像的每个像素,使用亮度匹配技术确定最佳匹配源像素。一旦找到最佳匹配源像素,它的色度值被分配给目标像素,而保留目标像素的原始亮度值。

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