Reduced-reference image quality assessment using distributed source coding

This paper presents a reduced-reference image quality assessment scheme using distributed source coding for remotely monitoring image quality. In our scheme, an image server extracts a feature vector from the original image and transmits its Slepian-Wolf syndrome using an LDPC encoder. With the rate of the Slepian-Wolf bitstream chosen according to a predetermined admissible image quality, the receiver can reconstruct the feature vector using its received image, as side information, as long as the quality is higher than the admissible quality. Thus the receiver can determine the received image quality using the reconstructed feature vector. Simulation results show that distributed source coding can reduce the bit-rate of the feature vector by 50% and achieve better compression performance than conventional source coding.