RGB Image Reconstruction Using Two-Separated Band Reject Filters

Abstract

Noises like impulse or Gaussian noise could be easily removed and recovered in the spatial domain by applying mean or median convolution. Structural noise, like periodic has a global degradation effect. This degradation is looking like bars that cover the image. This paper developed a new approach that detect the degradation; recover it; and hence reconstruct the original color image. The two dimensions discrete Fourier Transform is applied to isolate, block, and replace some particular frequencies (degradation bands) using auto detection and recovery procedure, it applies two separated band reject filters to avoid blocking the true bands like what is resulted in Ring filter. It tries locating the periodic noise (two spikes) and the four degraded lines using a powerful searching algorithm in the frequency domain. Unlike, Ring and Notch filter, the Two-Circle method is smart enough to predict the size of the spike, so a suitable band rejected filter should be selected to replace only degraded bands with approximation values instead of zeros. The Peak Signal to Noise Ratio (PSNR) vs. periodic frequency relation is applied to find the quality of measurements of the reconstructed and cleaned colored image. So, the quality of three methods is calculated and compared. All testing results show that the two separated band reject filters method satisfied maximum dB results and minimum frequency change to the steady state values than other two methods.