To boost the security of color image encryption algorithms and enlarge their key space, an encryption algorithm of color image based on cellular neural networks (CNNs) is proposed. The sequence produced by the 6D CNN system is segmented into two groups and combined at a specific ratio. The new chaotic sequence obtained is used as the key source for a 4D hyperchaos system. The key is selected based on the logical operation results of the plaintext pixel mean, and the final chaotic encryption sequences X and Y are obtained. Pixel scrambling, diffusion on each layer of R, G, B, and pixel value replacement encryption operations are performed on color images, which are encrypted as ciphertext images. The results of the experimental simulation demonstrate that the image encryption algorithm outlined in this paper possesses significant key space, robust sensitivity to both keys and plaintext, uniform distribution of ciphertext pixels, and a correlation coefficient near 0 among neighboring pixels. It is capable of effectively thwarting exhaustive attacks, statistical analysis attacks, and differential attacks, and produces a notable encryption impact on color images. It possesses specific utility in the realm of color image information security.