Research About Image Fast Colorization Algorithm Based On Intelligent Seed Pixel Selection

Colorization is a technique to automatically produce color components for monochrome images and videos based on a few input colors.Generally,image colorization is initialized from a number of seed pixels whose colors are specified by users,and then the colors are gradually propagating to the monochrome surroundings under a given optimization constraint.So,the performance of colorization is highly dependent on the selection of seed pixels.However,little attention has been paid to the selection of seed pixels,and how to improve the effectiveness of manual input remains a challenging task.To address this,an improved colorization method using seed pixel selection is proposed to assist the users in determining which pixels are highly required to be colorized for a high-quality colorized image.Specifically,the gray-scale image is first divided into non-overlapped blocks,and then,for each block,two pixels that approximate the average luminance of block are selected as the seeds.After the seed pixels are colored by users,an optimization that minimizes the difference between the seeds and their adjacent pixels is employed to propagate the colors to the other pixels.The experimental results demonstrate that,for a given amount of inputs,the proposed method can achieve a higher PSNR than the conventional colorization methods.Moreover,the proposed method is made further improvement:on the one hand,according to the proposed method,the selected seed pixels are colored manually by users,which is a complex work,affecting the practicality of the proposed method.In order to overcome the limitation,after obtain the seed pixels,without any manual input,the colors of seeds are directly obtained according to the similar image.On the other hand,the seed selection mechanism in the proposed method selects a fixed number of seeds for each block.In order to further improve the feasibility of seed number,the number of seeds selected in each block is adaptive,that is,selecting more seed points in complex block,and selecting only a small number of seeds in simple block.The experimental results confirm the feasibility and effectiveness of the two improvements.