In order to improve the robustness, reading speed and information hiding capacity of printed quantum dot images, the work aims to propose a reliable encoding and decoding algorithm for composite spectral printed quantum dot image. Firstly, ChaCha20 encryption algorithm, SHA-256 hash algorithm, (331, 225, 367) convolutional code and interlacing coding were combined to encode the plaintext information into binary secret information with security verification and error correction capabilities, and then pseudo random synchronization information was inserted, and mask matrix scrambling was carried out, which was mapped into a printed quantum dot image that could be solved jointly by adjacent data. Finally, two sets of printed quantum dot images were used to modulate the carrier image to realize the large-capacity information hiding of composite spectrum. The experimental results showed that the generated composite spectral printed quantum dot image could resist the noise attack within 20%, the reading time was about 0.1 s, the embedding rate was 2 bpp, and the Peak Signal-to-Noise Ratio (PSNR) value was about 40 dB compared with the original carrier image and the structural similarity (SSIM) value was about 0.97. Compared with other algorithms, this algorithm has higher robustness, better invisibility and faster reading speed under high embedding rate.