Residual Concatenated Network for ODBTC Image Restoration
Alim Wicaksono Hari Prayuda, Heri Prasetyo, Jing-Ming Guo · 2019
This paper proposes Residual Concatenated Network (RCN) for improving the quality of Ordered Dither Block Truncation Coding (ODBTC) decoded image. This method inherits the effectiveness of Convolutional Neural Networks (CNN) for suppressing the impulsive noise occurred in decoded image. It suppresses the noise by applying a series of convolutional operations. The network directly performs learning process via an end-to-end mapping approach. The experimental results reveal that the proposed approach yields a promising result in the ODBTC image restoration.