Colorization Grayscale Image Based on Zero Point

Image colorization is an important and difficult problem in image processing with various applications including image stylization and heritage restoration. Most existing image colorization methods utilize feature matching between the reference color image and the target grayscale image. The effectiveness of features is often significantly affected by the characteristics of the local image region. Most of the previous methods require some amount of user interventions, making colorization a hard work. Motivated by this, a novel automatic grayscale image colorization method based on histogram regression is presented in this paper. A source image is adopted to provide the color information. Locally weighted regression is performed on both the grayscale image and the source image. Thus, the feature distributions of two images can be obtained. Then, a new matching method is proposed to align these features by finding and adjusting the zero-points of the histogram. When the luminance-color correspondence was achieved, the grayscale image is colorized in a weighted way.

Keywords:

component , Colorization , Reference Color Image , Target Grayscale Image , Histogram Regression