As the barcode becomes more widely used, its applications and data capacity demands grow,
increasing the need for barcodes with greater data density. Utilizing the quick response (QR)
code–one of the many types of barcodes–we developed two algorithms. The first algorithm
creates a color QR code that stores more information than a standard QR code and embeds extra
data with limited access privilege. The second algorithm denoises a noisy color QR code. These
algorithms consist of three techniques: (1) enlarging the data capacity of a compact QR code
image by stacking multiple classical QR codes to form a color barcode, (2) embedding
information into the color QR code using pseudo quantum signals in an M-band wavelet domain
and selecting the discrete 4-band wavelet transforms to compress the QR images, and (3)
applying Discrete M-band Wavelet Transform (DMWT) and Patch Group Prior based Denoising
(PGPD) methods to denoise noisy QR code images. The peak-signal-to-noise-ratio (PSNR)
summary indicates that information in a color QR code can be efficiently stored and retrieved
with these methods. Moreover, it shows that our denoising algorithm effectively removes heavy
noise from the noisy color QR code. Our algorithms are implemented in a flexible framework,
which allows for further modifications to improve both the data capacity of a color QR code and
the effectiveness of signal extraction from noisy data to meet future demands.