Color space conversion algorithm and comparison study

Abstract

Purpose The advantages and disadvantages between various conversion algorithms are analyzed, and the relatively optimal conversion algorithm is obtained by comparing color difference, conversion accuracy, and operability. Method Using 729 sets of data from the K = 0% part of the ECI2002 standard color target as samples, experiment 2° was conducted under the D50 light source in the field of view, and the minimum, average, and maximum color differences of C, M, and Y were analyzed and compared by three unused color space conversion algorithms, and the operability of the three algorithms was also analyzed. Phenomenon Of the three algorithms, the polynomial regression algorithm and the neural network algorithm have similar errors, while the Nünchberg equation is less accurate and has a larger error. The operability of each of the three algorithms has advantages and disadvantages. Conclusion The polynomial regression algorithm has the highest accuracy, the lowest error, and the best method.