This paper presents a novel colorization method that significantly reduces the manual effort required for colorizing monochrome images and videos. The method is based on the principle that neighboring pixels with similar intensities should have similar colors. This premise is formalized using a quadratic cost function, which is solved efficiently through standard optimization techniques. Users only need to annotate a few color scribbles, and the algorithm automatically propagates these colors in both space and time to produce a fully colorized image or sequence. The approach is demonstrated to produce high-quality colorizations from minimal user input, making it a practical and user-friendly solution for both still images and video clips. The paper also compares the method to existing techniques, showing its robustness and effectiveness in handling complex boundaries and tracking failures.This paper presents a novel colorization method that significantly reduces the manual effort required for colorizing monochrome images and videos. The method is based on the principle that neighboring pixels with similar intensities should have similar colors. This premise is formalized using a quadratic cost function, which is solved efficiently through standard optimization techniques. Users only need to annotate a few color scribbles, and the algorithm automatically propagates these colors in both space and time to produce a fully colorized image or sequence. The approach is demonstrated to produce high-quality colorizations from minimal user input, making it a practical and user-friendly solution for both still images and video clips. The paper also compares the method to existing techniques, showing its robustness and effectiveness in handling complex boundaries and tracking failures.