LUM Smoother with Smooth Control for Noisy Image Sequences

Abstract

This paper focuses on adaptive structure of LUM (lower-upper-middle) smoothers for noisy image sequences. For the balance between noise suppression and signal-detail preservation, the LUM smoothers are widely used in smoothing applications. The amount of smoothing done by LUM smoothers is controlled by tuning parameter. However, the smoothing level is fixed for whole image. Thus, the excessive or insufficient smoothing can be performed. This problem is solved by a new method based on the adaptive controlled level of smoothing. A new method has excellent performance of the noise reduction in the environments corrupted by the impulse noise. In addition, minimal signal-detail and motion blurring can be observed. The performance of proposed method is evaluated through objective criteria and compared with traditional temporal, spatial, and spatiotemporal LUM smoothers.

Random impulse noise removal from image sequences based on fuzzy logic

“…In this subsection, the performance of the proposed method is compared to the following 3-D filters: the 3-D rational filter (RAT), 21 the adaptive 3-D median filter (A3DM), and the weighted 3-D median filter (W3DM), 22 the adaptive 3-D LUM smoother (LUM) 24 and the peak-and-valley filter (PAV). 23 Further, the proposed method is also compared to the 2-D fuzzy random impulse noise reduction method (FRINRM), 12 as a representative of the 2-D filters, to show that the proposed filter takes real advantage from the temporal information.…”

“…The LUM (lower-upper-middle) smoother in Ref. 24 extends the standard LUM smoothers 9 by introducing an adaptive smoothing control. Using a fixed smoothing level for a whole image namely results in excessive smoothing in some given regions and insufficient smoothing in other regions.…”