The goal of color and contrast enhancement in general is to provide a more appealing image or video by adjusting the amount of saturation and lightness to achieve more vivid or realistic colors and to increase the visibility of details that may be obscured by deficient global and local lightness. We implemented and compared the performance of various color and contrast enhancement algorithms using image difference maps in all three dimensions of lightness, chroma and hue, derived from IPT, a uniform, perceptual color space. The comparative analysis includes four published methods, two proprietary algorithms commonly used in consumer video applications and a new proposed approach developed as part of our research. Functionalities of these algorithms are evaluated with regard to the working requirements for an algorithm to be suitable for a typical video processing chain in consumer systems. We also report the results obtained from two psychophysical experiments involving the proprietary and proposed algorithms. Several still images and videos are used in the Method of Paired Comparison experiments to compare overall image/picture quality of various algorithm outputs. Results show a consistently satisfactory performance of the new algorithm, with opportunities for further improvement.