Transmission errors recovery of quantized images using fuzzy block similarity measures
Résumé
In addition to the source coding artifacts, the encoded bit streams representing codeword indexes of a vector quantized image are vulnerable to transmission or media impairments. Impulse block noise in the received images is the main artifact due to transmission errors. We use the fuzzy set theory to represent the vague concept of a block similarity with its spatial context. This approach is conducted in order to detect and to conceal the transmission errors. Error concealment by searching the best matching codeword is an attractive alternative to the commonly used interpolation approach. It reduces considerably the computational complexity at the receiver end. Simulation results show that the proposed method considerably improves the subjective quality of VQ images transmitted over noisy channels.