Reverse image filtering with clean and noisy filters

Adaptive Wiener filtering of noisy images and image sequences

In this work, we consider the adaptive Wiener filtering of noisy images and image sequences. We begin by using an adaptive weighted averaging (AWA) approach to estimate the second-order statistics required by the Wiener filter. Experimentally, the resulting Wiener filter is improved by about 1dB in the sense of peak-to-peak SNR (PSNR). Also, the subjective improvement is significant in that the...

Adaptive motion-compensated filtering of noisy image sequences

Assessment of SAR Image Filtering Using Adaptive Stack Filters

Stack filters are a special case of non-linear filters. They have a good performance for filtering images with different types of noise while preserving edges and details. A stack filter decomposes an input image into several binary images according to a set of thresholds. Each binary image is then filtered by a Boolean function, which characterizes the filter. Adaptive stack filters can be des...

Multichannel adaptive L-filters in color image filtering

Three novel adaptive multichannel L-filters based on marginal data ordering are proposed. They rely on well-known algorithms for the unconstrained minimization of the Mean Squared Error (MSE), namely, the Least Mean Squares (LMS), the normalized LMS (NLMS) and the LMS-Newton (LMSN) algorithm. Performance comparisons in color image filtering have been made both in RGB and U∗V ∗W ∗ color spaces. ...

Noisy Image Restoration Based on Boundary Resetting BDND and Median Filtering with Smallest Window

In this paper, a restoration approach for noisy image is proposed where a boundary resetting boundary discriminative noise detection (BRBDND) and a median filtering with smallest window (MFSW) are applied. In the proposed image restoration approach, two stages are involved: noise detection and noise replacement. The BRBDND is used to detect noisy pixels in an image. If a pixel is uncorrupted, t...