Adaptive Rate Polar Code for DCT-Based Digital Image Transmission

Polar code is a recent forward error correction technique that is characterized by its low encoding/decoding complexity and good error performance. In this paper, a complete image transmission system (transmitter and receiver) is proposed to improve the image quality over different types of channels such as Gaussian, Rayleigh and Rician channels. The proposed system is based on encoding the most significant quantized Discrete Cosine Transform (DCT) coefficients of the digital image using adaptive rate polar coding, by changing the number of frozen bits depending on the number of significant DCT coefficients that depend on the channel quality. Simulation results reveal that the proposed system achieves better performance compared to the coded digital transmission schemes in terms of the Structural SIMilarity (SSIM) index and the Peak Signal to Noise Ratio (PSNR) for different sizes of images. Moreover, it is not subject to “cliff effect” and exhibits improvement in image quality according to the channel quality.